{"id":96053,"date":"2026-08-27T11:02:43","date_gmt":"2026-08-27T03:02:43","guid":{"rendered":"https:\/\/www.wsisp.com\/helps\/96053.html"},"modified":"2026-08-27T11:02:43","modified_gmt":"2026-08-27T03:02:43","slug":"%ef%bc%88%e8%ae%ba%e6%96%87%e9%80%9f%e8%af%bb%ef%bc%89consistency-models%ef%bc%9a%e6%8a%8a%e6%89%a9%e6%95%a3%e6%a8%a1%e5%9e%8b%e7%9a%84%e8%bf%ad%e4%bb%a3%e7%94%9f%e6%88%90%e5%8e%8b%e7%bc%a9%e5%88%b0","status":"publish","type":"post","link":"https:\/\/www.wsisp.com\/helps\/96053.html","title":{"rendered":"\uff08\u8bba\u6587\u901f\u8bfb\uff09Consistency Models\uff1a\u628a\u6269\u6563\u6a21\u578b\u7684\u8fed\u4ee3\u751f\u6210\u538b\u7f29\u5230\u4e00\u6b65"},"content":{"rendered":"<p>\u8bba\u6587\u9898\u76ee&#xff1a; Consistency Models&#xff08;\u4e00\u81f4\u6027\u6a21\u578b&#xff09;<br \/>\n\u4f1a\u8bae&#xff1a; ICML 2023<\/p>\n<p>\u6458\u8981&#xff1a; \u6269\u6563\u6a21\u578b\u6781\u5927\u63a8\u52a8\u4e86\u56fe\u50cf\u3001\u97f3\u9891\u548c\u89c6\u9891\u751f\u6210\u7684\u53d1\u5c55&#xff0c;\u4f46\u5b83\u4eec\u4f9d\u8d56\u8fed\u4ee3\u5f0f\u91c7\u6837\u8fc7\u7a0b&#xff0c;\u56e0\u6b64\u751f\u6210\u901f\u5ea6\u8f83\u6162\u3002\u4e3a\u89e3\u51b3\u8fd9\u4e00\u9650\u5236&#xff0c;\u672c\u6587\u63d0\u51fa Consistency Models&#xff08;\u4e00\u81f4\u6027\u6a21\u578b&#xff09;&#xff0c;\u4e00\u79cd\u80fd\u591f\u5c06\u566a\u58f0\u76f4\u63a5\u6620\u5c04\u5230\u6570\u636e\u7684\u65b0\u578b\u751f\u6210\u6a21\u578b\u3002Consistency Models \u5929\u751f\u652f\u6301\u5feb\u901f\u7684\u4e00\u6b65\u751f\u6210&#xff0c;\u540c\u65f6\u4e5f\u5141\u8bb8\u91c7\u7528\u591a\u6b65\u91c7\u6837&#xff0c;\u5728\u8ba1\u7b97\u91cf\u4e0e\u6837\u672c\u8d28\u91cf\u4e4b\u95f4\u8fdb\u884c\u6743\u8861\u3002\u5b83\u8fd8\u652f\u6301\u96f6\u6837\u672c\u6570\u636e\u7f16\u8f91&#xff0c;\u4f8b\u5982\u56fe\u50cf\u4fee\u590d\u3001\u7740\u8272\u548c\u8d85\u5206\u8fa8\u7387&#xff0c;\u800c\u65e0\u9700\u9488\u5bf9\u8fd9\u4e9b\u4efb\u52a1\u8fdb\u884c\u663e\u5f0f\u8bad\u7ec3\u3002Consistency Models \u65e2\u53ef\u4ee5\u901a\u8fc7\u84b8\u998f\u9884\u8bad\u7ec3\u6269\u6563\u6a21\u578b\u8fdb\u884c\u8bad\u7ec3&#xff0c;\u4e5f\u53ef\u4ee5\u5b8c\u5168\u72ec\u7acb\u5730\u4f5c\u4e3a\u751f\u6210\u6a21\u578b\u8bad\u7ec3\u3002\u5927\u91cf\u5b9e\u9a8c\u8868\u660e&#xff0c;\u5728\u4e00\u6b65\u548c\u5c11\u6b65\u91c7\u6837\u573a\u666f\u4e0b&#xff0c;\u5b83\u4f18\u4e8e\u5df2\u6709\u7684\u6269\u6563\u6a21\u578b\u84b8\u998f\u6280\u672f&#xff0c;\u4e00\u6b65\u751f\u6210\u5728 CIFAR-10 \u548c ImageNet 64 \u00d7 64 \u4e0a\u5206\u522b\u53d6\u5f97 FID &#061; 3.55 \u548c FID &#061; 6.20\u3002\u5f53\u72ec\u7acb\u8bad\u7ec3\u65f6&#xff0c;Consistency Models \u6784\u6210\u4e86\u4e00\u7c7b\u65b0\u7684\u751f\u6210\u6a21\u578b&#xff0c;\u5728 CIFAR-10\u3001ImageNet 64 \u00d7 64 \u548c LSUN 256 \u00d7 256 \u7b49\u6807\u51c6\u57fa\u51c6\u4e0a\u80fd\u591f\u8d85\u8fc7\u5df2\u6709\u7684\u4e00\u6b65\u3001\u975e\u5bf9\u6297\u5f0f\u751f\u6210\u6a21\u578b\u3002<\/p>\n<hr \/>\n<h3>\u4e00\u3001\u7814\u7a76\u80cc\u666f\u4e0e\u6838\u5fc3\u95ee\u9898&#xff1a;\u6269\u6563\u6a21\u578b\u6548\u679c\u5f88\u597d&#xff0c;\u4f46\u4e3a\u4ec0\u4e48\u4e00\u5b9a\u8981\u4e00\u6b65\u4e00\u6b65\u53bb\u566a&#xff1f;<\/h3>\n<p>\u6269\u6563\u6a21\u578b\u7684\u751f\u6210\u903b\u8f91\u5927\u5bb6\u5df2\u7ecf\u6bd4\u8f83\u719f\u6089&#xff1a;\u5148\u4ece\u968f\u673a\u566a\u58f0\u51fa\u53d1&#xff0c;\u7136\u540e\u4e0d\u65ad\u8c03\u7528\u795e\u7ecf\u7f51\u7edc\u8fdb\u884c\u53bb\u566a&#xff0c;\u6700\u7ec8\u5f97\u5230\u771f\u5b9e\u6570\u636e\u3002\u95ee\u9898\u5728\u4e8e&#xff0c;\u8fd9\u79cd\u201c\u9010\u6b65\u751f\u6210\u201d\u7684\u673a\u5236\u867d\u7136\u5e26\u6765\u4e86\u5f88\u9ad8\u7684\u751f\u6210\u8d28\u91cf&#xff0c;\u5374\u4e5f\u5929\u7136\u5e26\u6765\u4e86\u63a8\u7406\u901f\u5ea6\u74f6\u9888\u3002<\/p>\n<p>\u8bba\u6587\u6307\u51fa&#xff0c;\u4e0e GAN\u3001VAE\u3001Normalizing Flow \u8fd9\u7c7b\u5355\u6b65\u751f\u6210\u6a21\u578b\u76f8\u6bd4&#xff0c;\u4f20\u7edf\u6269\u6563\u6a21\u578b\u7684\u91c7\u6837\u901a\u5e38\u9700\u8981 10&#xff5e;2000 \u500d\u7684\u8ba1\u7b97\u91cf\u3002\u5373\u4f7f\u4f7f\u7528\u66f4\u5feb\u7684 ODE Solver&#xff0c;\u60f3\u83b7\u5f97\u6709\u7ade\u4e89\u529b\u7684\u6837\u672c\u8d28\u91cf&#xff0c;\u5f80\u5f80\u4ecd\u7136\u9700\u8981\u5341\u6b21\u4ee5\u4e0a\u7f51\u7edc\u8bc4\u4f30\u3002<br \/>\n\u4f46\u8fd9\u91cc\u6709\u4e00\u4e2a\u5f88\u5bb9\u6613\u88ab\u5ffd\u7565\u7684\u95ee\u9898&#xff1a;\u6269\u6563\u6a21\u578b\u7684\u201c\u591a\u6b65\u201d\u4e0d\u4ec5\u662f\u7f3a\u70b9\u3002<\/p>\n<p>\u591a\u6b65\u63a8\u7406\u540c\u65f6\u5e26\u6765\u4e86\u4e24\u4e2a\u5f88\u91cd\u8981\u7684\u80fd\u529b\u3002\u7b2c\u4e00&#xff0c;\u53ef\u4ee5\u901a\u8fc7\u589e\u52a0\u91c7\u6837\u6b65\u6570&#xff0c;\u7528\u66f4\u591a\u8ba1\u7b97\u6362\u66f4\u9ad8\u7684\u56fe\u50cf\u8d28\u91cf&#xff1b;\u7b2c\u4e8c&#xff0c;\u5f88\u591a Zero-Shot \u56fe\u50cf\u7f16\u8f91\u80fd\u529b&#xff0c;\u4f8b\u5982 Inpainting\u3001Colorization\u3001Super-Resolution\u3001SDEdit&#xff0c;\u672c\u8d28\u4e0a\u90fd\u4f9d\u8d56\u8fd9\u79cd\u8fed\u4ee3\u5f0f\u91c7\u6837\u8fc7\u7a0b\u3002<\/p>\n<p>\u6240\u4ee5\u8fd9\u7bc7\u8bba\u6587\u771f\u6b63\u60f3\u89e3\u51b3\u7684\u5e76\u4e0d\u662f\u7b80\u5355\u7684&#xff1a;<\/p>\n<p>\u201c\u600e\u6837\u628a\u6269\u6563\u6a21\u578b\u52a0\u901f&#xff1f;\u201d<\/p>\n<p>\u800c\u662f\u4e00\u4e2a\u66f4\u82db\u523b\u7684\u95ee\u9898&#xff1a;<\/p>\n<p>\u80fd\u4e0d\u80fd\u8bbe\u8ba1\u4e00\u79cd\u751f\u6210\u6a21\u578b&#xff0c;\u9ed8\u8ba4\u4e00\u6b65\u5c31\u80fd\u4ece\u566a\u58f0\u5f97\u5230\u6570\u636e&#xff0c;\u4f46\u9700\u8981\u7684\u65f6\u5019\u4ecd\u7136\u53ef\u4ee5\u591a\u6b65\u751f\u6210&#xff0c;\u800c\u4e14\u8fd8\u80fd\u4fdd\u7559\u6269\u6563\u6a21\u578b\u7684 Zero-Shot \u7f16\u8f91\u80fd\u529b&#xff1f;<\/p>\n<p>\u8fd9\u5c31\u662f Consistency Models \u7684\u51fa\u53d1\u70b9\u3002<\/p>\n<p>\u4f5c\u8005\u7684\u5173\u952e\u6d1e\u5bdf\u6765\u81ea\u8fde\u7eed\u65f6\u95f4\u6269\u6563\u6a21\u578b\u91cc\u7684 Probability Flow ODE&#xff08;PF ODE&#xff09;\u3002<\/p>\n<p>\u5bf9\u4e8e\u6269\u6563\u6a21\u578b&#xff0c;\u6570\u636e\u5206\u5e03\u53ef\u4ee5\u901a\u8fc7 SDE \u4e0d\u65ad\u52a0\u5165 Gaussian Noise&#xff1b;\u4e0e\u6b64\u540c\u65f6&#xff0c;\u5b58\u5728\u4e00\u6761\u5177\u6709\u76f8\u540c\u8fb9\u7f18\u5206\u5e03\u7684 PF ODE\u3002\u8bba\u6587\u91c7\u7528 Karras et al. \u7684\u8bbe\u5b9a\u540e&#xff0c;\u7ecf\u9a8c PF ODE \u53ef\u4ee5\u5199\u6210&#xff1a;<\/p>\n<p style=\"text-align:center\"><img loading=\"lazy\" decoding=\"async\" alt=\"\" height=\"60\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/08\/20260827030240-6a8fa8d0c3062.png\" width=\"176\" \/><\/p>\n<p>\u5176\u4e2d (<img decoding=\"async\" alt=\"s_\\\\phi(x_t,t)\" class=\"mathcode\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/08\/20260827030240-6a8fa8d0d4c7e.png\" \/>) \u662f\u8bad\u7ec3\u597d\u7684 Score Model&#xff0c;\u5b83\u8fd1\u4f3c\u5f53\u524d\u566a\u58f0\u5206\u5e03\u7684 Score Function\u3002\u4f20\u7edf\u505a\u6cd5\u9700\u8981\u4ece (<img decoding=\"async\" alt=\"x_T\" class=\"mathcode\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/08\/20260827030240-6a8fa8d0e1061.png\" \/>) \u51fa\u53d1&#xff0c;\u7528 Euler\u3001Heun \u7b49\u6570\u503c ODE Solver \u4e00\u6b65\u4e00\u6b65\u6c42\u89e3\u5230 (<img decoding=\"async\" alt=\"x_\\\\epsilon\" class=\"mathcode\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/08\/20260827030240-6a8fa8d0ed0ba.png\" \/>)\u3002<\/p>\n<p>Consistency Models \u7684\u601d\u8def\u5374\u662f&#xff1a;\u65e2\u7136\u540c\u4e00\u6761 PF ODE \u8f68\u8ff9\u4e0a\u7684\u6240\u6709\u70b9\u6700\u7ec8\u90fd\u4f1a\u56de\u5230\u540c\u4e00\u4e2a\u8d77\u70b9&#xff0c;\u90a3\u4e48\u4e3a\u4ec0\u4e48\u4e0d\u76f4\u63a5\u5b66\u4e60\u201c\u8f68\u8ff9\u4e0a\u7684\u4efb\u610f\u4e00\u70b9 \u2192 \u8d77\u70b9\u201d\u8fd9\u4e2a\u6620\u5c04&#xff1f;<\/p>\n<p>\u8fd9\u4e00\u6b65&#xff0c;\u57fa\u672c\u5c31\u662f\u6574\u7bc7\u8bba\u6587\u6700\u6838\u5fc3\u7684\u601d\u60f3\u3002<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" alt=\"\" height=\"374\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/08\/20260827030241-6a8fa8d104b19.png\" width=\"1044\" \/><\/p>\n<p>\u8bba\u6587 Figure 1&#xff1a;PF ODE \u8f68\u8ff9\u4e0e Consistency Model \u7684\u57fa\u672c\u601d\u60f3<\/p>\n<p>Figure 1 \u60f3\u8868\u8fbe\u7684\u5176\u5b9e\u5f88\u7b80\u5355&#xff1a;\u540c\u4e00\u6761 PF ODE \u8f68\u8ff9\u4e0a\u7684 (<img decoding=\"async\" alt=\"x_t\" class=\"mathcode\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/08\/20260827030241-6a8fa8d14ae42.png\" \/>)\u3001(<img decoding=\"async\" alt=\"x_{t&apos;}\" class=\"mathcode\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/08\/20260827030241-6a8fa8d156ec9.png\" \/>)\u3001(<img decoding=\"async\" alt=\"x_T\" class=\"mathcode\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/08\/20260827030240-6a8fa8d0e1061.png\" \/>)&#xff0c;\u65e0\u8bba\u4ece\u54ea\u4e2a\u4f4d\u7f6e\u5f00\u59cb&#xff0c;\u90fd\u5e94\u8be5\u6620\u5c04\u5230\u540c\u4e00\u4e2a\u6570\u636e\u7aef\u70b9 (<img decoding=\"async\" alt=\"x_0\" class=\"mathcode\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/08\/20260827030241-6a8fa8d162d94.png\" \/>)\u3002\u56e0\u6b64\u6a21\u578b\u9700\u8981\u5b66\u4e60\u7684\u4e0d\u662f\u201c\u4e0b\u4e00\u6b65\u5f80\u54ea\u91cc\u8d70\u201d&#xff0c;\u800c\u662f\u201c\u8fd9\u6761\u8f68\u8ff9\u6700\u7ec8\u4ece\u54ea\u91cc\u51fa\u53d1\u201d\u3002<\/p>\n<hr \/>\n<h3>\u4e8c\u3001Consistency Model \u5230\u5e95\u5728\u5b66\u4ec0\u4e48&#xff1a;\u6838\u5fc3\u4e0d\u662f Denoising&#xff0c;\u800c\u662f Self-Consistency<\/h3>\n<h4>2.1 Consistency Function&#xff1a;\u4e00\u6761\u8f68\u8ff9\u4e0a\u7684\u6240\u6709\u70b9&#xff0c;\u90fd\u5e94\u8be5\u8f93\u51fa\u540c\u4e00\u4e2a\u7ed3\u679c<\/h4>\n<p>\u7ed9\u5b9a PF ODE \u4e0a\u7684\u4e00\u6761\u8f68\u8ff9 (<img loading=\"lazy\" decoding=\"async\" alt=\"\" height=\"22\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/08\/20260827030241-6a8fa8d16eb8c.png\" width=\"69\" \/>)&#xff0c;\u8bba\u6587\u5b9a\u4e49 Consistency Function&#xff1a;<\/p>\n<p class=\"img-center\"><img loading=\"lazy\" decoding=\"async\" alt=\"\" height=\"33\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/08\/20260827030241-6a8fa8d17b907.png\" width=\"176\" \/><\/p>\n<p>\u4e5f\u5c31\u662f\u8bf4&#xff0c;\u4e0d\u7ba1\u8f93\u5165\u7684\u662f\u566a\u58f0\u5f88\u5927\u7684 (<img decoding=\"async\" alt=\"x_T\" class=\"mathcode\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/08\/20260827030240-6a8fa8d0e1061.png\" \/>)&#xff0c;\u8fd8\u662f\u5df2\u7ecf\u63a5\u8fd1\u6570\u636e\u7aef\u7684 (<img decoding=\"async\" alt=\"x_t\" class=\"mathcode\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/08\/20260827030241-6a8fa8d14ae42.png\" \/>)&#xff0c;\u6a21\u578b\u90fd\u8bd5\u56fe\u76f4\u63a5\u9884\u6d4b\u8fd9\u6761 ODE \u8f68\u8ff9\u7684\u8d77\u70b9 (<img decoding=\"async\" alt=\"x_\\\\epsilon\" class=\"mathcode\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/08\/20260827030240-6a8fa8d0ed0ba.png\" \/>)\u3002<\/p>\n<p>\u56e0\u6b64&#xff0c;\u5982\u679c (<img decoding=\"async\" alt=\"x_t\" class=\"mathcode\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/08\/20260827030241-6a8fa8d14ae42.png\" \/>) \u4e0e (<img decoding=\"async\" alt=\"x_{t&apos;}\" class=\"mathcode\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/08\/20260827030241-6a8fa8d156ec9.png\" \/>) \u4f4d\u4e8e\u540c\u4e00\u6761 PF ODE \u8f68\u8ff9&#xff0c;\u90a3\u4e48\u5fc5\u987b\u6ee1\u8db3&#xff1a;<\/p>\n<p style=\"text-align:center\"><img decoding=\"async\" alt=\"f(x_t,t)=f(x_{t&apos;},t&apos;)\" class=\"mathcode\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/08\/20260827030241-6a8fa8d1897fb.png\" \/><\/p>\n<p>\u8fd9\u5c31\u662f\u8bba\u6587\u6240\u8c13\u7684 Self-Consistency&#xff08;\u81ea\u4e00\u81f4\u6027&#xff09;\u3002<\/p>\n<p class=\"img-center\"><img loading=\"lazy\" decoding=\"async\" alt=\"\" height=\"220\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/08\/20260827030241-6a8fa8d196727.png\" width=\"503\" \/><\/p>\n<p>\u8bba\u6587 Figure 2&#xff1a;Consistency Model \u5c06\u540c\u4e00\u6761 PF ODE \u8f68\u8ff9\u4e0a\u7684\u4e0d\u540c\u70b9\u6620\u5c04\u5230\u540c\u4e00\u4e2a\u8d77\u70b9<\/p>\n<p>Figure 2 \u662f\u7406\u89e3\u5168\u6587\u6700\u91cd\u8981\u7684\u4e00\u5f20\u56fe\u3002\u4f20\u7edf\u6269\u6563\u6a21\u578b\u66f4\u50cf\u662f\u5728\u5b66\u4e60\u4e00\u4e2a\u5c40\u90e8\u65b9\u5411&#xff1a;\u5f53\u524d\u4f4d\u7f6e\u5e94\u8be5\u600e\u6837\u7ee7\u7eed\u53bb\u566a&#xff1b;Consistency Model \u5219\u76f4\u63a5\u5b66\u4e60\u4e00\u4e2a\u5168\u5c40\u6620\u5c04&#xff1a;\u5f53\u524d\u4f4d\u7f6e\u5c5e\u4e8e\u54ea\u6761\u8f68\u8ff9&#xff0c;\u8fd9\u6761\u8f68\u8ff9\u7684\u6570\u636e\u7aef\u70b9\u5728\u54ea\u91cc\u3002<\/p>\n<p>\u8fd9\u4e5f\u89e3\u91ca\u4e86\u4e3a\u4ec0\u4e48\u5b83\u53ef\u4ee5\u4e00\u6b65\u751f\u6210\u3002\u6d4b\u8bd5\u65f6\u76f4\u63a5\u91c7\u6837 (<img decoding=\"async\" alt=\"x_T\\\\sim\\\\mathcal N(0,T^2I)\" class=\"mathcode\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/08\/20260827030241-6a8fa8d1dbda4.png\" \/>)&#xff0c;\u7136\u540e\u53ea\u6267\u884c\u4e00\u6b21&#xff1a;<\/p>\n<p style=\"text-align:center\"><img loading=\"lazy\" decoding=\"async\" alt=\"\" height=\"41\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/08\/20260827030241-6a8fa8d1e7d8e.png\" width=\"214\" \/><\/p>\n<p>\u4e00\u6b21\u7f51\u7edc\u524d\u5411\u4f20\u64ad\u5c31\u5b8c\u6210\u4e86\u4ece Gaussian Noise \u5230\u6570\u636e\u6837\u672c\u7684\u6620\u5c04\u3002<\/p>\n<h4>2.2 Boundary Condition&#xff1a;\u6a21\u578b\u4e0d\u80fd\u5728\u6570\u636e\u7aef\u628a\u6837\u672c\u6539\u574f<\/h4>\n<p>Consistency Function \u8fd8\u5fc5\u987b\u6ee1\u8db3\u4e00\u4e2a\u8fb9\u754c\u6761\u4ef6&#xff1a;<\/p>\n<p style=\"text-align:center\"><img decoding=\"async\" alt=\"f(x_\\\\epsilon,\\\\epsilon)=x_\\\\epsilon\" class=\"mathcode\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/08\/20260827030242-6a8fa8d2023b0.png\" \/><\/p>\n<p>\u76f4\u89c2\u7406\u89e3\u5c31\u662f&#xff1a;\u5f53\u8f93\u5165\u5df2\u7ecf\u5904\u5728\u8f68\u8ff9\u7684\u6570\u636e\u7aef\u65f6&#xff0c;\u6a21\u578b\u4ec0\u4e48\u4e5f\u4e0d\u8981\u505a&#xff0c;\u76f4\u63a5\u8f93\u51fa\u8f93\u5165\u672c\u8eab\u3002<\/p>\n<p>\u4e3a\u4e86\u81ea\u52a8\u6ee1\u8db3\u8fd9\u4e2a\u6761\u4ef6&#xff0c;\u8bba\u6587\u6700\u7ec8\u91c7\u7528 Skip Connection \u53c2\u6570\u5316&#xff1a;<\/p>\n<p class=\"img-center\"><img loading=\"lazy\" decoding=\"async\" alt=\"\" height=\"30\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/08\/20260827030242-6a8fa8d20dc90.png\" width=\"277\" \/><\/p>\n<p>\u5176\u4e2d\u8981\u6c42 (<img decoding=\"async\" alt=\"c_{\\\\mathrm{skip}}(\\\\epsilon)=1\" class=\"mathcode\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/08\/20260827030242-6a8fa8d21d7b1.png\" \/>)&#xff0c;(<img decoding=\"async\" alt=\"c_{\\\\mathrm{out}}(\\\\epsilon)=0\" class=\"mathcode\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/08\/20260827030242-6a8fa8d22b803.png\" \/>)\u3002\u4e8e\u662f\u5f53 (<img decoding=\"async\" alt=\"t=\\\\epsilon\" class=\"mathcode\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/08\/20260827030242-6a8fa8d2385b0.png\" \/>) \u65f6&#xff0c;\u4e0d\u7ba1\u795e\u7ecf\u7f51\u7edc (<img decoding=\"async\" alt=\"F_\\\\theta\" class=\"mathcode\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/08\/20260827030242-6a8fa8d244782.png\" \/>) \u8f93\u51fa\u4ec0\u4e48&#xff0c;\u90fd\u6709 (<img decoding=\"async\" alt=\"f_\\\\theta(x,\\\\epsilon)=x\" class=\"mathcode\" src=\"2026-08-27qp5hjgsdrkv.png\" \/>)\u3002<\/p>\n<p>\u8fd9\u4e2a\u8bbe\u8ba1\u770b\u8d77\u6765\u53ea\u662f\u4e00\u4e2a\u5de5\u7a0b\u7ec6\u8282&#xff0c;\u5b9e\u9645\u4e0a\u975e\u5e38\u5173\u952e\u3002\u8bba\u6587\u540e\u9762\u7684\u7406\u8bba\u5206\u6790\u6307\u51fa&#xff0c;\u8be5\u8fb9\u754c\u6761\u4ef6\u80fd\u591f\u6392\u9664 (<img decoding=\"async\" alt=\"f_\\\\theta(x,t)\\\\equiv0\" class=\"mathcode\" src=\"2026-08-27k5hyhxd0luu.png\" \/>) \u8fd9\u6837\u7684 trivial solution&#xff0c;\u5426\u5219\u53ea\u9760\u201c\u4e00\u81f4\u6027\u201d\u5f88\u5bb9\u6613\u51fa\u73b0\u6240\u6709\u8f93\u5165\u90fd\u8f93\u51fa\u540c\u4e00\u4e2a\u4e1c\u897f\u8fd9\u79cd\u65e0\u610f\u4e49\u89e3\u3002<\/p>\n<h4>2.3 \u4e3a\u4ec0\u4e48\u4e00\u6b65\u6a21\u578b\u4ecd\u7136\u53ef\u4ee5\u591a\u6b65\u91c7\u6837&#xff1f;<\/h4>\n<p>Consistency Models \u5e76\u6ca1\u6709\u56e0\u4e3a\u652f\u6301\u4e00\u6b65\u751f\u6210&#xff0c;\u5c31\u628a\u591a\u6b65\u751f\u6210\u80fd\u529b\u6254\u6389\u3002<\/p>\n<p>Algorithm 1 \u7684\u505a\u6cd5\u662f\u5148\u6267\u884c\u4e00\u6b21&#xff1a;<\/p>\n<p style=\"text-align:center\"><img decoding=\"async\" alt=\"x\\\\leftarrow f_\\\\theta(\\\\hat{x}_T,T)\" class=\"mathcode\" src=\"2026-08-27du3pfr1czmw.png\" \/><\/p>\n<p>\u5982\u679c\u60f3\u7ee7\u7eed\u63d0\u5347\u8d28\u91cf&#xff0c;\u5c31\u91cd\u65b0\u5411\u5f53\u524d\u7ed3\u679c\u52a0\u5165\u4e00\u5b9a\u5f3a\u5ea6\u7684 Gaussian Noise&#xff0c;\u518d\u8c03\u7528 Consistency Model \u6620\u5c04\u56de\u6570\u636e\u7aef&#xff0c;\u5982\u6b64\u5faa\u73af&#xff1a;<\/p>\n<p style=\"text-align:center\"><img decoding=\"async\" alt=\"x \\\\rightarrow \\\\text{add noise }\\\\tau_1 \\\\rightarrow f_\\\\theta \\\\rightarrow \\\\text{add noise }\\\\tau_2 \\\\rightarrow f_\\\\theta \\\\rightarrow\\\\cdots\" class=\"mathcode\" src=\"2026-08-27o1f1bagfslu.png\" \/><\/p>\n<p>\u56e0\u6b64\u5b83\u5f62\u6210\u4e86\u4e00\u79cd\u5f88\u6709\u610f\u601d\u7684\u63a8\u7406\u65b9\u5f0f&#xff1a;\u4e00\u6b65\u751f\u6210\u662f\u9ed8\u8ba4\u80fd\u529b&#xff0c;\u591a\u6b65\u751f\u6210\u5219\u662f\u53ef\u9009\u7684\u8d28\u91cf\u589e\u5f3a\u673a\u5236\u3002<\/p>\n<p>\u8bba\u6587\u5b9e\u9645\u901a\u8fc7 Greedy Search &#043; Ternary Search \u9010\u4e2a\u9009\u62e9\u591a\u6b65\u91c7\u6837\u4e2d\u7684\u65f6\u95f4\u70b9&#xff0c;\u4f7f\u91c7\u6837 FID \u5c3d\u53ef\u80fd\u4f4e\u3002\u4f5c\u8005\u540c\u65f6\u660e\u786e\u6307\u51fa&#xff0c;\u8fd9\u91cc\u5047\u8bbe\u4e0b\u4e00\u65f6\u95f4\u70b9\u5bf9\u5e94\u7684 FID \u8fd1\u4f3c\u4e3a\u5355\u5cf0\u51fd\u6570&#xff0c;\u66f4\u4f18\u7684\u65f6\u95f4\u70b9\u9009\u62e9\u7b56\u7565\u7559\u4f5c\u672a\u6765\u5de5\u4f5c\u3002<\/p>\n<hr \/>\n<h3>\u4e09\u3001Consistency Distillation&#xff1a;\u600e\u6837\u628a\u4e00\u4e2a\u6269\u6563\u6a21\u578b\u538b\u7f29\u6210\u4e00\u6b65\u751f\u6210\u5668&#xff1f;<\/h3>\n<p>Consistency Models \u63d0\u4f9b\u4e86\u4e24\u79cd\u5b8c\u5168\u4e0d\u540c\u7684\u8bad\u7ec3\u65b9\u5f0f\u3002<\/p>\n<p>\u7b2c\u4e00\u79cd\u53eb Consistency Distillation&#xff08;CD&#xff09;&#xff1a;\u5df2\u7ecf\u6709\u4e00\u4e2a\u8bad\u7ec3\u597d\u7684 Diffusion \/ Score Model&#xff0c;\u73b0\u5728\u5e0c\u671b\u628a\u5b83\u7684 PF ODE \u52a8\u529b\u5b66\u538b\u7f29\u8fdb Consistency Model\u3002<\/p>\n<p>\u7b2c\u4e8c\u79cd\u53eb Consistency Training&#xff08;CT&#xff09;&#xff1a;\u5b8c\u5168\u4e0d\u8981\u9884\u8bad\u7ec3\u6269\u6563\u6a21\u578b&#xff0c;\u76f4\u63a5\u4ece\u771f\u5b9e\u6570\u636e\u8bad\u7ec3 Consistency Model\u3002<\/p>\n<p>\u5148\u770b\u66f4\u5bb9\u6613\u7406\u89e3\u7684 CD\u3002<\/p>\n<h4>3.1 CD \u7684\u6838\u5fc3&#xff1a;\u8ba9\u76f8\u90bb\u8f68\u8ff9\u70b9\u5f97\u5230\u76f8\u540c\u9884\u6d4b<\/h4>\n<p>\u5c06\u65f6\u95f4\u533a\u95f4 ([<img decoding=\"async\" alt=\"\\\\epsilon,T\" class=\"mathcode\" src=\"2026-08-2723puyzgi51u.png\" \/>]) \u79bb\u6563\u6210&#xff1a;<\/p>\n<p style=\"text-align:center\"><img decoding=\"async\" alt=\"t_1=\\\\epsilon&lt;t_2&lt;\\\\cdots&lt;t_N=T\" class=\"mathcode\" src=\"2026-08-27ixeor2adkbl.png\" \/><\/p>\n<p>\u5047\u8bbe\u73b0\u5728\u6709\u4e00\u4e2a\u5e26\u566a\u6837\u672c (<img decoding=\"async\" alt=\"x_{t_{n+1}}\" class=\"mathcode\" src=\"2026-08-27sl2s2ccrtom.png\" \/>)\u3002\u5229\u7528\u9884\u8bad\u7ec3 Score Model \u548c\u4e00\u4e2a ODE Solver&#xff0c;\u53ef\u4ee5\u4ece (<img decoding=\"async\" alt=\"t_{n+1}\" class=\"mathcode\" src=\"2026-08-27okklgbeqnkb.png\" \/>) \u5411\u524d\u8d70\u4e00\u6b65&#xff0c;\u5f97\u5230\u5bf9\u524d\u4e00\u4e2a\u8f68\u8ff9\u70b9 (<img decoding=\"async\" alt=\"x_{t_n}\" class=\"mathcode\" src=\"2026-08-27ke0rbbjqr0r.png\" \/>) \u7684\u4f30\u8ba1&#xff1a;<\/p>\n<p class=\"img-center\"><img loading=\"lazy\" decoding=\"async\" alt=\"\" height=\"39\" src=\"2026-08-27vpbmxswk4se.png\" width=\"453\" \/><\/p>\n<p>\u8fd9\u91cc (<img decoding=\"async\" alt=\"\\\\Phi\" class=\"mathcode\" src=\"2026-08-27sbm3qjhjv3a.png\" \/>) \u5c31\u662f\u4e00\u9636 ODE Solver \u7684\u66f4\u65b0\u51fd\u6570\u3002<\/p>\n<p>\u5982\u679c Consistency Model \u771f\u7684\u5b66\u5230\u4e86 Self-Consistency&#xff0c;\u90a3\u4e48\u540c\u4e00\u6761\u8f68\u8ff9\u4e0a\u76f8\u90bb\u7684\u4e24\u4e2a\u4f4d\u7f6e (<img decoding=\"async\" alt=\"x_{t_{n+1}}\" class=\"mathcode\" src=\"2026-08-27sl2s2ccrtom.png\" \/>) \u548c (<img decoding=\"async\" alt=\"\\\\hat{x}^{\\\\phi}_{t_n}\" class=\"mathcode\" src=\"2026-08-2723qhnkxcata.png\" \/>)&#xff0c;\u7ecf\u8fc7\u6a21\u578b\u4ee5\u540e\u5c31\u5e94\u8be5\u7ed9\u51fa\u76f8\u540c\u7684\u6570\u636e\u7aef\u9884\u6d4b\u3002<\/p>\n<p>\u56e0\u6b64\u8bba\u6587\u5b9a\u4e49 Consistency Distillation Loss&#xff1a;<\/p>\n<p class=\"img-center\"><img loading=\"lazy\" decoding=\"async\" alt=\"\" height=\"75\" src=\"2026-08-27e0tzwcm5hht.png\" width=\"481\" \/><\/p>\n<p>\u5176\u4e2d (<img decoding=\"async\" alt=\"f_\\\\theta\" class=\"mathcode\" src=\"2026-08-27lyzympwrbow.png\" \/>) \u662f Online Network&#xff0c;(<img decoding=\"async\" alt=\"f_{\\\\theta^-}\" class=\"mathcode\" src=\"2026-08-27jsvmtsg4ttv.png\" \/>) \u662f Target Network&#xff0c;(<img decoding=\"async\" alt=\"d(\\\\cdot,\\\\cdot)\" class=\"mathcode\" src=\"2026-08-27gvgwkq2x4sv.png\" \/>) \u662f\u4e24\u4e2a\u8f93\u51fa\u4e4b\u95f4\u7684\u8ddd\u79bb\u3002\u8bad\u7ec3\u65f6&#xff0c;Online Network \u6b63\u5e38\u68af\u5ea6\u66f4\u65b0&#xff0c;\u800c Target Network \u4f7f\u7528 EMA \u66f4\u65b0&#xff0c;\u5e76\u914d\u5408 Stop Gradient\u3002<\/p>\n<p>\u8fd9\u5957\u7ed3\u6784\u548c Deep Q-Learning\u3001Momentum Contrastive Learning \u4e2d\u7684 Target Network \u975e\u5e38\u76f8\u4f3c\u3002\u4f5c\u8005\u53d1\u73b0&#xff0c;\u76f8\u6bd4\u76f4\u63a5\u4ee4 (<img decoding=\"async\" alt=\"\\\\theta^-=\\\\theta\" class=\"mathcode\" src=\"2026-08-2715cvsmektp3.png\" \/>)&#xff0c;EMA &#043; StopGrad \u53ef\u4ee5\u660e\u663e\u7a33\u5b9a\u8bad\u7ec3\u5e76\u6539\u5584\u6700\u7ec8\u6027\u80fd\u3002<\/p>\n<p>\u6240\u4ee5 CD \u53ef\u4ee5\u538b\u7f29\u6210\u4e00\u53e5\u8bdd&#xff1a;<\/p>\n<p>\u5148\u7528\u9884\u8bad\u7ec3\u6269\u6563\u6a21\u578b\u544a\u8bc9\u4f60\u201c\u76f8\u90bb\u4e24\u4e2a PF ODE \u8f68\u8ff9\u70b9\u5728\u54ea\u91cc\u201d&#xff0c;\u518d\u8981\u6c42 Consistency Model \u4ece\u8fd9\u4e24\u4e2a\u4f4d\u7f6e\u7ed9\u51fa\u76f8\u540c\u7684\u6570\u636e\u7aef\u9884\u6d4b\u3002<\/p>\n<h4>3.2 \u7406\u8bba\u4e0a\u4e3a\u4ec0\u4e48\u8fd9\u6837\u771f\u7684\u80fd\u5b66\u5230 PF ODE \u7684 Consistency Function&#xff1f;<\/h4>\n<p>\u8bba\u6587\u7684 Theorem 1 \u7ed9\u51fa\u4e86\u6bd4\u8f83\u91cd\u8981\u7684\u7406\u8bba\u7ed3\u679c&#xff1a;\u5047\u8bbe Consistency Model \u6ee1\u8db3 Lipschitz \u6761\u4ef6&#xff0c;\u800c\u6240\u4f7f\u7528\u7684 ODE Solver \u662f (p) \u9636\u65b9\u6cd5&#xff0c;\u90a3\u4e48\u5f53 Consistency Distillation Loss \u8fbe\u5230 0 \u65f6&#xff0c;\u6a21\u578b\u4e0e\u771f\u5b9e Consistency Function \u4e4b\u95f4\u7684\u6700\u5927\u8bef\u5dee\u91cf\u7ea7\u4e3a (<img decoding=\"async\" alt=\"O((\\\\Delta t)^p)\" class=\"mathcode\" src=\"2026-08-27s1obtucd0sw.png\" \/>)\u3002<\/p>\n<p>\u76f4\u89c2\u6765\u8bf4\u5c31\u662f&#xff1a;<\/p>\n<p>\u65f6\u95f4\u79bb\u6563\u8d8a\u7ec6&#xff0c;ODE Solver \u9636\u6570\u8d8a\u9ad8&#xff0c;\u901a\u8fc7 CD \u5b66\u5230\u7684 Consistency Model \u5c31\u8d8a\u63a5\u8fd1\u771f\u5b9e PF ODE \u4e0a\u5bf9\u5e94\u7684 Consistency Function\u3002<\/p>\n<p>\u8fd9\u4e2a\u7406\u8bba\u7ed3\u8bba\u968f\u540e\u4e5f\u5f97\u5230\u4e86 Figure 3 \u5b9e\u9a8c\u7684\u652f\u6301&#xff1a;\u540c\u6837\u7684\u79bb\u6563\u6b65\u6570 (N) \u4e0b&#xff0c;\u4e8c\u9636 Heun Solver \u59cb\u7ec8\u4f18\u4e8e\u4e00\u9636 Euler Solver\u3002<\/p>\n<hr \/>\n<h3>\u56db\u3001Consistency Training&#xff1a;\u6ca1\u6709 Teacher Diffusion Model&#xff0c;\u4e5f\u80fd\u76f4\u63a5\u8bad\u7ec3\u5417&#xff1f;<\/h3>\n<p>CD \u4ecd\u7136\u6709\u4e00\u4e2a\u9650\u5236&#xff1a;\u5b83\u867d\u7136\u628a\u63a8\u7406\u53d8\u6210\u4e86\u4e00\u6b65&#xff0c;\u4f46\u8bad\u7ec3\u4e4b\u524d\u8fd8\u662f\u5f97\u5148\u6709\u4e00\u4e2a\u5f3a\u5927\u7684 Diffusion Model\u3002<\/p>\n<p>\u4f5c\u8005\u66f4\u8fdb\u4e00\u6b65\u63d0\u51fa&#xff1a;<\/p>\n<p>Consistency Model \u80fd\u4e0d\u80fd\u4e0d\u518d\u53ea\u662f Diffusion Distillation&#xff0c;\u800c\u662f\u81ea\u5df1\u6210\u4e3a\u4e00\u4e2a\u72ec\u7acb\u7684\u751f\u6210\u6a21\u578b&#xff1f;<\/p>\n<p>\u8fd9\u5c31\u662f Consistency Training&#xff08;CT&#xff09;\u3002<\/p>\n<h4>4.1 \u4ece Score Function \u7684\u65e0\u504f\u4f30\u8ba1\u5f00\u59cb<\/h4>\n<p>CD \u4f9d\u8d56\u9884\u8bad\u7ec3 Score Model (<img decoding=\"async\" alt=\"s_\\\\phi(x_t,t)\" class=\"mathcode\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/08\/20260827030240-6a8fa8d0d4c7e.png\" \/>) \u53bb\u4f30\u8ba1 (<img decoding=\"async\" alt=\"\\\\nabla\\\\log p_t(x_t)\" class=\"mathcode\" src=\"2026-08-27hromzvhjviz.png\" \/>)\u3002<\/p>\n<p>\u8bba\u6587\u5229\u7528\u4e86\u4e00\u4e2a\u5173\u952e\u5173\u7cfb&#xff1a;<\/p>\n<p class=\"img-center\"><img loading=\"lazy\" decoding=\"async\" alt=\"\" height=\"50\" src=\"2026-08-27u1fyeg1xnqo.png\" width=\"256\" \/><\/p>\n<p>\u5176\u4e2d\u771f\u5b9e\u6570\u636e (<img decoding=\"async\" alt=\"x\\\\sim p_{\\\\mathrm{data}}\" class=\"mathcode\" src=\"2026-08-27wjzjxg0fowk.png\" \/>)&#xff0c;\u5e76\u4e14 (<img decoding=\"async\" alt=\"x_t\\\\sim\\\\mathcal N(x,t^2I)\" class=\"mathcode\" src=\"2026-08-27tua3jlb0hjq.png\" \/>)\u3002<\/p>\n<p>\u4e5f\u5c31\u662f\u8bf4&#xff0c;\u53ea\u8981\u6709\u771f\u5b9e\u6837\u672c (x) \u548c Gaussian Noise&#xff0c;\u5c31\u53ef\u4ee5\u5229\u7528 (<img decoding=\"async\" alt=\"-(x_t-x)\/t^2\" class=\"mathcode\" src=\"2026-08-27reczd0k3avv.png\" \/>) \u6784\u9020 Score Function \u7684\u65e0\u504f\u4f30\u8ba1&#xff0c;\u800c\u4e0d\u4e00\u5b9a\u8981\u8ba9\u4e00\u4e2a\u9884\u8bad\u7ec3\u795e\u7ecf\u7f51\u7edc\u63d0\u4f9b Score\u3002<\/p>\n<p>\u7ecf\u8fc7\u7406\u8bba\u63a8\u5bfc&#xff0c;\u4f5c\u8005\u53d1\u73b0&#xff0c;\u5f53\u4f7f\u7528 Euler Solver \u4e14\u65f6\u95f4\u79bb\u6563\u8d8b\u4e8e\u65e0\u7a77\u7ec6\u65f6&#xff0c;Consistency Distillation Loss \u53ef\u4ee5\u7531\u4e00\u4e2a\u5b8c\u5168\u4e0d\u542b Teacher \u53c2\u6570 (<img decoding=\"async\" alt=\"\\\\phi\" class=\"mathcode\" src=\"2026-08-27lp44uy4zz2l.png\" \/>) \u7684 Consistency Training Loss \u8fd1\u4f3c&#xff1a;<\/p>\n<p class=\"img-center\"><img loading=\"lazy\" decoding=\"async\" alt=\"\" height=\"29\" src=\"2026-08-27wvhyf550l2v.png\" width=\"406\" \/><\/p>\n<p>\u5176\u4e2d (<img decoding=\"async\" alt=\"z\\\\sim\\\\mathcal N(0,I)\" class=\"mathcode\" src=\"2026-08-27fbgmnoud11m.png\" \/>)\u3002<\/p>\n<p>\u8fd9\u4e2a\u516c\u5f0f\u5176\u5b9e\u5f88\u597d\u7406\u89e3\u3002<\/p>\n<p>\u4ece\u4e00\u4e2a\u771f\u5b9e\u6837\u672c (x) \u51fa\u53d1&#xff0c;\u91c7\u6837\u540c\u4e00\u4e2a\u566a\u58f0 (z)&#xff0c;\u5206\u522b\u6309\u7167 (<img decoding=\"async\" alt=\"t_n\" class=\"mathcode\" src=\"2026-08-27aovgxddhw4f.png\" \/>) \u548c (<img decoding=\"async\" alt=\"t_{n+1}\" class=\"mathcode\" src=\"2026-08-27okklgbeqnkb.png\" \/>) \u4e24\u4e2a\u5f3a\u5ea6\u52a0\u566a&#xff1a;<\/p>\n<p style=\"text-align:center\"><img decoding=\"async\" alt=\"x \\\\rightarrow x+t_nz\" class=\"mathcode\" src=\"2026-08-27creejlu1amo.png\" \/><\/p>\n<p style=\"text-align:center\"><img decoding=\"async\" alt=\"x \\\\rightarrow x+t_{n+1}z\" class=\"mathcode\" src=\"2026-08-27auxi4wdcaiv.png\" \/><\/p>\n<p>\u5b83\u4eec\u53ef\u4ee5\u88ab\u7406\u89e3\u4e3a\u540c\u4e00\u6761\u5c40\u90e8\u566a\u58f0\u8def\u5f84\u4e0a\u7684\u4e24\u4e2a\u72b6\u6001\u3002CT \u5c31\u8981\u6c42\u6a21\u578b\u4ece\u8fd9\u4e24\u4e2a\u72b6\u6001\u6062\u590d\u51fa\u4e00\u81f4\u7684\u7ed3\u679c\u3002\u8fd9\u6837\u4e00\u6765&#xff1a;<\/p>\n<p>\u771f\u5b9e\u6570\u636e &#043; Gaussian Noise &#043; Self-Consistency Training&#xff0c;\u5c31\u53ef\u4ee5\u66ff\u4ee3 Teacher Diffusion Model\u3002<\/p>\n<p>\u8fd9\u4e5f\u662f\u8bba\u6587\u4e3a\u4ec0\u4e48\u5f3a\u8c03 Consistency Models \u4e0d\u4ec5\u662f\u4e00\u79cd Distillation Technique&#xff0c;\u800c\u53ef\u4ee5\u6210\u4e3a\u4e00\u4e2a\u72ec\u7acb Generative Model\u3002<\/p>\n<h4>4.2 CT \u6700\u5927\u7684\u5de5\u7a0b\u95ee\u9898&#xff1a;N \u600e\u4e48\u9009&#xff1f;<\/h4>\n<p>CT \u4e2d\u6709\u4e00\u4e2a\u975e\u5e38\u91cd\u8981\u7684 Bias-Variance Trade-off\u3002<\/p>\n<p>\u5f53\u65f6\u95f4\u79bb\u6563\u6b65\u6570 (N) \u6bd4\u8f83\u5c0f\u65f6&#xff0c;\u76f8\u90bb\u65f6\u95f4\u70b9\u8ddd\u79bb\u8f83\u8fdc&#xff0c;\u8bad\u7ec3\u76ee\u6807\u5177\u6709\u66f4\u5927\u7684 Bias&#xff0c;\u4f46 Variance \u8f83\u4f4e&#xff0c;\u56e0\u6b64\u6bd4\u8f83\u5bb9\u6613\u4f18\u5316\u3001\u6536\u655b\u5f88\u5feb&#xff1b;\u5f53 (N) \u5f88\u5927\u65f6&#xff0c;\u79bb\u6563\u8bef\u5dee\u66f4\u5c0f&#xff0c;Bias \u66f4\u4f4e&#xff0c;\u4f46\u8bad\u7ec3\u76ee\u6807\u7684 Variance \u589e\u5927&#xff0c;\u4f18\u5316\u53cd\u800c\u66f4\u56f0\u96be\u3002<\/p>\n<p>\u4f5c\u8005\u56e0\u6b64\u6ca1\u6709\u56fa\u5b9a (N)&#xff0c;\u800c\u662f\u91c7\u7528 Progressive Schedule&#xff1a;<\/p>\n<p>\u8bad\u7ec3\u65e9\u671f\u4f7f\u7528\u8f83\u5c0f\u7684 N&#xff0c;\u8ba9\u6a21\u578b\u5feb\u901f\u6536\u655b&#xff1b;\u8bad\u7ec3\u540e\u671f\u9010\u6e10\u589e\u5927 N&#xff0c;\u964d\u4f4e\u79bb\u6563\u8bef\u5dee\u3002<\/p>\n<p>\u4e0e\u6b64\u540c\u65f6&#xff0c;Target Network \u7684 EMA \u7cfb\u6570 (<img decoding=\"async\" alt=\"\\\\mu\" class=\"mathcode\" src=\"2026-08-27o2x1rndwr0c.png\" \/>) \u4e5f\u968f (N) \u4e00\u8d77\u53d8\u5316\u3002<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" alt=\"\" height=\"366\" src=\"2026-08-27spkvdeilqgz.png\" width=\"1590\" \/><\/p>\n<p>\u8bba\u6587 Figure 3&#xff1a;CD \u548c CT \u7684\u5173\u952e\u8bbe\u8ba1\u6d88\u878d<\/p>\n<p>Figure 3 \u662f\u5168\u6587\u6700\u91cd\u8981\u7684\u6d88\u878d\u56fe\u4e4b\u4e00&#xff0c;\u91cc\u9762\u53ef\u4ee5\u5f97\u5230\u56db\u4e2a\u5f88\u660e\u786e\u7684\u7ed3\u8bba&#xff1a;<\/p>\n<li>\n<p>CD \u4f7f\u7528 LPIPS \u660e\u663e\u4f18\u4e8e \u21131 \u548c \u21132&#xff1b;<\/p>\n<\/li>\n<li>\n<p>\u76f8\u540c (N) \u4e0b&#xff0c;Heun Solver \u4f18\u4e8e Euler&#xff1b;<\/p>\n<\/li>\n<li>\n<p>CD \u4e2d (N&#061;18) \u8868\u73b0\u6700\u597d&#xff0c;\u800c\u4e14\u5f53 (N) \u8db3\u591f\u5927\u540e&#xff0c;\u5bf9 (N) \u4e0d\u518d\u7279\u522b\u654f\u611f&#xff1b;<\/p>\n<\/li>\n<li>\n<p>CT \u5bf9 (N) \u975e\u5e38\u654f\u611f&#xff0c;\u91c7\u7528\u52a8\u6001\u589e\u957f\u7684 (N) \u548c (\\\\mu) \u540e&#xff0c;\u6536\u655b\u901f\u5ea6\u548c\u6700\u7ec8\u751f\u6210\u8d28\u91cf\u660e\u663e\u6539\u5584\u3002<br \/>\n\u8fd9\u4e00\u7ec4\u6d88\u878d\u5f88\u91cd\u8981&#xff0c;\u56e0\u4e3a\u5b83\u5e76\u4e0d\u53ea\u662f\u544a\u8bc9\u6211\u4eec\u201c\u67d0\u4e2a\u8d85\u53c2\u6570\u8bbe\u7f6e\u66f4\u597d\u201d&#xff0c;\u800c\u662f\u76f4\u63a5\u9a8c\u8bc1\u4e86\u524d\u9762\u7684\u7406\u8bba&#xff1a;CD \u7684\u8bef\u5dee\u4e0e ODE Solver \u7cbe\u5ea6\u6709\u5173&#xff0c;\u800c CT \u7684\u5173\u952e\u56f0\u96be\u662f\u79bb\u6563 Bias \u4e0e\u4f18\u5316 Variance \u4e4b\u95f4\u7684\u5e73\u8861\u3002<\/p>\n<\/li>\n<hr \/>\n<h3>\u4e94\u3001\u5b9e\u9a8c\u7ed3\u679c\u4e0e\u6d88\u878d\u5206\u6790&#xff1a;\u4e00\u6b65\u751f\u6210\u5230\u5e95\u80fd\u505a\u5230\u4ec0\u4e48\u7a0b\u5ea6&#xff1f;<\/h3>\n<p>\u8bba\u6587\u5728 CIFAR-10\u3001ImageNet 64 \u00d7 64\u3001LSUN Bedroom 256 \u00d7 256 \u548c LSUN Cat 256 \u00d7 256 \u4e0a\u8fdb\u884c\u4e86\u5b9e\u9a8c&#xff0c;\u4e3b\u8981\u4f7f\u7528 FID\u3001IS\u3001Precision \u548c Recall \u8bc4\u4f30\u751f\u6210\u8d28\u91cf\u3002FID \u8d8a\u4f4e\u8d8a\u597d&#xff0c;IS\u3001Precision \u548c Recall \u8d8a\u9ad8\u8d8a\u597d\u3002<\/p>\n<p>\u8fd9\u91cc\u8981\u660e\u786e\u533a\u5206\u4e24\u4e2a\u5b9e\u9a8c\u76ee\u6807&#xff1a;<\/p>\n<ul>\n<li>\n<p>CD \u8981\u56de\u7b54&#xff1a;\u80fd\u4e0d\u80fd\u628a\u4e00\u4e2a\u5df2\u6709 Diffusion Model \u84b8\u998f\u6210\u9ad8\u8d28\u91cf\u7684\u4e00\u6b65\/\u5c11\u6b65\u6a21\u578b&#xff1f;<\/p>\n<\/li>\n<li>\n<p>CT \u8981\u56de\u7b54&#xff1a;\u5b8c\u5168\u4e0d\u4f9d\u8d56\u9884\u8bad\u7ec3 Diffusion Model \u65f6&#xff0c;Consistency Model \u80fd\u4e0d\u80fd\u72ec\u7acb\u6210\u4e3a\u751f\u6210\u6a21\u578b&#xff1f;<\/p>\n<\/li>\n<\/ul>\n<h4>5.1 Figure 4&#xff1a;CD \u5bf9 Progressive Distillation \u7684\u4f18\u52bf\u975e\u5e38\u660e\u663e<\/h4>\n<p>\u4e0e CD \u6700\u76f4\u63a5\u7684\u5bf9\u624b\u662f Progressive Distillation&#xff08;PD&#xff09;\u3002<\/p>\n<p>\u76f8\u6bd4\u4e00\u4e9b\u9700\u8981\u63d0\u524d\u8ba9 Diffusion Model \u751f\u6210\u5927\u89c4\u6a21 Synthetic Dataset \u518d\u8fdb\u884c\u84b8\u998f\u7684\u65b9\u6cd5&#xff0c;CD \u548c PD \u90fd\u53ef\u4ee5\u76f4\u63a5\u5229\u7528\u539f\u6a21\u578b\u8fdb\u884c\u84b8\u998f&#xff0c;\u4e0d\u9700\u8981\u63d0\u524d\u6784\u9020\u989d\u5916\u751f\u6210\u6570\u636e\u3002\u8bba\u6587\u4fdd\u8bc1 PD \u4e0e CD \u84b8\u998f\u7684\u662f\u540c\u4e00\u6279 EDM Teacher&#xff0c;\u56e0\u6b64\u6bd4\u8f83\u76f8\u5bf9\u516c\u5e73\u3002<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" alt=\"\" height=\"444\" src=\"2026-08-27uyvsdqclmyz.png\" width=\"1601\" \/><\/p>\n<p>\u8bba\u6587 Figure 4&#xff1a;CD \u4e0e PD \u5728\u4e0d\u540c\u6570\u636e\u96c6\u3001\u4e0d\u540c\u91c7\u6837\u6b65\u6570\u4e0b\u7684 FID \u5bf9\u6bd4<\/p>\n<p>Figure 4 \u7684\u7ed3\u679c\u975e\u5e38\u76f4\u89c2&#xff1a;\u968f\u7740\u91c7\u6837\u6b65\u6570\u589e\u52a0&#xff0c;PD \u548c CD \u90fd\u4f1a\u53d8\u597d&#xff0c;\u4f46 CD \u5728\u51e0\u4e4e\u6240\u6709\u6570\u636e\u96c6\u3001\u91c7\u6837\u6b65\u6570\u548c\u8ddd\u79bb\u51fd\u6570\u8bbe\u7f6e\u4e0b\u90fd\u4f18\u4e8e PD\u3002\u552f\u4e00\u4f8b\u5916\u662f LSUN Bedroom 256 \u00d7 256 \u7684\u4e00\u6b65\u751f\u6210\u4e2d&#xff0c;\u4f7f\u7528 \u21132 \u7684 CD \u7565\u5dee\u4e8e\u4f7f\u7528 \u21132 \u7684 PD\u3002<br \/>\n\u6240\u4ee5\u8bba\u6587\u7684\u7ed3\u8bba\u5e76\u4e0d\u662f\u201cConsistency Model \u6240\u6709\u60c5\u51b5\u4e0b\u5168\u9762\u9886\u5148\u201d&#xff0c;\u800c\u662f&#xff1a;<\/p>\n<p>\u5728\u4f5c\u8005\u6d4b\u8bd5\u7684\u5927\u90e8\u5206 few-step diffusion distillation \u573a\u666f\u4e2d&#xff0c;CD \u90fd\u6bd4 PD \u66f4\u6709\u6548&#xff0c;\u800c\u4e14\u4f18\u52bf\u5728\u4e00\u6b65\u548c\u4e24\u6b65\u8fd9\u79cd\u6781\u4f4e NFE \u533a\u57df\u5c24\u5176\u660e\u663e\u3002<\/p>\n<h4>5.2 Table 1&#xff1a;CIFAR-10 \u4e00\u6b65 FID &#061; 3.55&#xff0c;\u4e24\u6b65\u5df2\u7ecf\u5230 2.93<\/h4>\n<p>Table 1 \u662f\u5168\u6587\u6700\u503c\u5f97\u8bb0\u4f4f\u7684\u4e00\u5f20\u7ed3\u679c\u8868\u3002<\/p>\n<p>\u5728 CIFAR-10 \u4e0a&#xff1a;<\/p>\n<p class=\"img-center\"><img loading=\"lazy\" decoding=\"async\" alt=\"\" height=\"814\" src=\"2026-08-27l2vkbitkzvz.png\" width=\"477\" \/><\/p>\n<p>\u6700\u660e\u663e\u7684\u662f CD&#xff1a;\u4e00\u6b65 FID \u4ece PD \u7684 8.34 \u964d\u5230\u4e86 3.55&#xff0c;\u4e24\u6b65\u8fdb\u4e00\u6b65\u964d\u5230 2.93\u3002<\/p>\n<p>\u800c Teacher EDM \u81ea\u5df1\u9700\u8981 35 \u6b21\u7f51\u7edc\u8bc4\u4f30\u624d\u80fd\u8fbe\u5230 FID &#061; 2.04\u3002\u6362\u53e5\u8bdd\u8bf4&#xff0c;CD \u7528\u6781\u5c11\u7684 NFE \u4fdd\u7559\u4e86\u76f8\u5f53\u4e00\u90e8\u5206 Teacher \u7684\u751f\u6210\u80fd\u529b\u3002<\/p>\n<p>\u5f53\u7136&#xff0c;\u4e0d\u80fd\u628a FID &#061; 3.55 \u5199\u6210\u201c\u8d85\u8fc7\u6240\u6709\u5355\u6b65\u751f\u6210\u6a21\u578b\u201d\u3002Table 1 \u4e2d StyleGAN2-ADA \u7684 FID &#061; 2.92&#xff0c;StyleGAN-XL \u66f4\u8fbe\u5230 1.85\u3002Consistency Model \u7684\u4f18\u52bf\u91cd\u70b9\u4e0d\u662f\u51fb\u8d25\u6700\u5f3a GAN&#xff0c;\u800c\u662f\u5728\u975e\u5bf9\u6297\u8bad\u7ec3 &#043; \u4e00\u6b65\/\u5c11\u6b65\u751f\u6210 &#043; \u591a\u6b65\u53ef\u6269\u5c55 &#043; Zero-Shot \u7f16\u8f91\u8fd9\u51e0\u79cd\u80fd\u529b\u4e4b\u95f4\u53d6\u5f97\u4e86\u65b0\u7684\u7ec4\u5408\u3002<\/p>\n<h4>5.3 Table 2&#xff1a;ImageNet \u548c LSUN \u4e0a&#xff0c;CD \u7684\u4f18\u52bf\u7ee7\u7eed\u4fdd\u6301<\/h4>\n<p class=\"img-center\"><img loading=\"lazy\" decoding=\"async\" alt=\"\" height=\"713\" src=\"2026-08-27m1cvynnc5ku.png\" width=\"425\" \/><\/p>\n<p>ImageNet 64 \u00d7 64 \u4e0a&#xff1a;<\/p>\n<ul>\n<li>\n<p>PD \u4e00\u6b65 FID &#061; 15.39&#xff0c;CD \u4e00\u6b65\u964d\u5230 6.20&#xff1b;<\/p>\n<\/li>\n<li>\n<p>PD \u4e24\u6b65 FID &#061; 8.95&#xff0c;CD \u4e24\u6b65\u8fdb\u4e00\u6b65\u964d\u5230 4.70\u3002<\/p>\n<\/li>\n<\/ul>\n<p>LSUN Bedroom 256 \u00d7 256 \u4e0a&#xff0c;CD \u4e00\u6b65\u548c\u4e24\u6b65\u5206\u522b\u8fbe\u5230 7.80 \/ 5.22&#xff1b;LSUN Cat 256 \u00d7 256 \u4e0a\u5206\u522b\u8fbe\u5230 11.0 \/ 8.84\u3002<\/p>\n<p>\u8fd9\u91cc\u5c24\u5176\u80fd\u770b\u51fa Consistency Distillation \u4e0e Progressive Distillation \u7684\u5dee\u8ddd\u3002\u4f8b\u5982 Cat \u6570\u636e\u96c6\u4e0a\u4e00\u9636\u751f\u6210&#xff0c;PD \u7684 FID \u662f 29.6&#xff0c;\u800c CD \u662f 11.0&#xff1b;\u5230\u4e86\u4e24\u6b65&#xff0c;PD \u662f 15.5&#xff0c;CD \u5df2\u7ecf\u964d\u5230 8.84\u3002<\/p>\n<p>\u56e0\u6b64&#xff0c;\u5982\u679c\u53ea\u770b\u8fd9\u7bc7\u8bba\u6587\u6700\u5f3a\u7684\u5b9e\u9a8c\u7ed3\u8bba&#xff0c;\u53ef\u4ee5\u6982\u62ec\u4e3a&#xff1a;<\/p>\n<p>Consistency Distillation \u628a Diffusion Model \u538b\u5230 1&#xff5e;2 \u6b21\u7f51\u7edc\u8bc4\u4f30\u65f6&#xff0c;\u751f\u6210\u8d28\u91cf\u663e\u8457\u4f18\u4e8e\u6b64\u524d\u7684 Progressive Distillation\u3002<\/p>\n<h4>5.4 CT&#xff1a;\u4e0d\u9760 Teacher \u80fd\u751f\u6210&#xff0c;\u4f46\u8d28\u91cf\u4e0e CD \u4ecd\u6709\u660e\u663e\u5dee\u8ddd<\/h4>\n<p>CT \u7684\u610f\u4e49\u548c CD \u4e0d\u4e00\u6837&#xff0c;\u5b83\u6ca1\u6709 Teacher Diffusion Model&#xff0c;\u56e0\u6b64\u4e0d\u80fd\u53ea\u7528\u6700\u7ec8 FID \u4e0e CD \u786c\u6bd4\u8f83\u3002<\/p>\n<p>CIFAR-10 \u4e0a CT \u7684\u4e00\u6b65 FID &#061; 8.70\u3001\u4e24\u6b65 FID &#061; 5.83&#xff1b;ImageNet \u4e0a\u5206\u522b\u4e3a 13.0 \u548c 11.1&#xff1b;LSUN Bedroom \u4e3a 16.0 \u548c 7.85&#xff1b;LSUN Cat \u4e3a 20.7 \u548c 11.7\u3002<br \/>\n\u8fd9\u4e9b\u6570\u5b57\u660e\u663e\u5f31\u4e8e CD&#xff0c;\u4f46 CT \u5b8c\u5168\u6ca1\u6709\u8bbf\u95ee\u9884\u8bad\u7ec3 Diffusion Teacher\u3002<\/p>\n<p>\u8bba\u6587\u6307\u51fa&#xff0c;\u5728 CIFAR-10 \u4e0a&#xff0c;CT \u5df2\u7ecf\u660e\u663e\u4f18\u4e8e Glow\u3001Residual Flow\u3001DenseFlow\u3001DC-VAE \u7b49\u4e00\u6b65\u3001\u975e\u5bf9\u6297\u751f\u6210\u6a21\u578b&#xff0c;\u540c\u65f6\u53ef\u4ee5\u8fbe\u5230\u4e0e\u4e00\u6b65 PD \u76f8\u8fd1\u7684\u8d28\u91cf\u3002\u53e6\u4e00\u65b9\u9762&#xff0c;StyleGAN \u7cfb\u5217\u4ecd\u7136\u660e\u663e\u66f4\u5f3a&#xff0c;\u56e0\u6b64\u8fd9\u91cc\u66f4\u51c6\u786e\u7684\u8bf4\u6cd5\u662f&#xff1a;CT \u8bc1\u660e\u4e86 Consistency Model \u53ef\u4ee5\u8131\u79bb Diffusion Distillation \u72ec\u7acb\u5b58\u5728&#xff0c;\u4f46\u5b83\u5728\u672c\u6587\u7248\u672c\u4e2d\u8fd8\u6ca1\u6709\u53d6\u4ee3\u6700\u5f3a GAN \u6216\u591a\u6b65 Diffusion Model\u3002<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" alt=\"\" height=\"521\" src=\"2026-08-27hxvf15rpv3x.png\" width=\"1281\" \/><\/p>\n<p>\u8bba\u6587 Figure 5&#xff1a;EDM\u3001CT \u4e00\u6b65\u751f\u6210\u548c CT \u4e24\u6b65\u751f\u6210\u7684\u6837\u672c<\/p>\n<p>Figure 5 \u8fd8\u6709\u4e00\u4e2a\u6709\u610f\u601d\u7684\u73b0\u8c61&#xff1a;\u4f5c\u8005\u8ba9 EDM\u3001\u4e00\u6b65 CT \u548c\u4e24\u6b65 CT \u4f7f\u7528\u76f8\u540c\u521d\u59cb Noise&#xff0c;\u7ed3\u679c\u5bf9\u5e94\u6837\u672c\u4e4b\u95f4\u4fdd\u6301\u4e86\u660e\u663e\u7684\u7ed3\u6784\u76f8\u4f3c\u6027\u3002\u867d\u7136 CT \u4e0e EDM \u662f\u72ec\u7acb\u8bad\u7ec3\u7684&#xff0c;\u4f5c\u8005\u4ecd\u636e\u6b64\u8ba4\u4e3a CT \u4e0d\u592a\u53ef\u80fd\u5b58\u5728\u4e25\u91cd Mode Collapse\u3002<\/p>\n<h4>5.5 Figure 7&#xff1a;\u79bb\u6563\u65f6\u95f4\u4e0e\u8fde\u7eed\u65f6\u95f4\u76ee\u6807\u5e76\u4e0d\u662f\u8c01\u90fd\u5168\u9762\u66f4\u5f3a<\/h4>\n<p class=\"img-center\"><img loading=\"lazy\" decoding=\"async\" alt=\"\" height=\"246\" src=\"2026-08-27f4f2bhan334.png\" width=\"546\" \/><\/p>\n<p>\u8bba\u6587 Appendix \u8fd8\u4e13\u95e8\u6bd4\u8f83\u4e86 Discrete-Time \u548c Continuous-Time \u7684 CD \/ CT\u3002<\/p>\n<p>Figure 7a \u4e2d&#xff0c;Continuous-Time CD \u91c7\u7528 StopGrad \u540e\u660e\u663e\u4f18\u4e8e\u4e0d\u4f7f\u7528 StopGrad \u7684\u7248\u672c&#xff0c;LPIPS \u4ecd\u7136\u662f\u6700\u4f73\u8ddd\u79bb\u51fd\u6570&#xff1b;\u4e0d\u8fc7\u6700\u7ec8 Discrete-Time CD \u4ecd\u7136\u4f18\u4e8e Continuous-Time CD\u3002\u4f5c\u8005\u8ba4\u4e3a\u5176\u4e2d\u4e00\u4e2a\u539f\u56e0\u662f Continuous-Time Objective \u65b9\u5dee\u66f4\u5927&#xff0c;\u800c\u79bb\u6563 CD \u53c8\u80fd\u591f\u76f4\u63a5\u4f7f\u7528\u9ad8\u9636 ODE Solver\u3002<\/p>\n<p>Figure 7b \u5219\u51fa\u73b0\u4e86\u4e0d\u540c\u7ed3\u679c&#xff1a;\u5728\u76f8\u540c LPIPS \u4e0b&#xff0c;Continuous-Time CT \u4f18\u4e8e Discrete-Time CT\u3002\u4f5c\u8005\u8ba4\u4e3a&#xff0c;\u8fd9\u662f\u56e0\u4e3a\u79bb\u6563 CT \u5b58\u5728\u6709\u9650 (<img decoding=\"async\" alt=\"\\\\Delta t\" class=\"mathcode\" src=\"2026-08-27mz23kj02yya.png\" \/>) \u5e26\u6765\u7684 Bias&#xff0c;\u800c\u8fde\u7eed\u65f6\u95f4\u76ee\u6807\u7b49\u4ef7\u4e8e\u8ba9 (<img decoding=\"async\" alt=\"\\\\Delta t\\\\to0\" class=\"mathcode\" src=\"2026-08-27dv4f5olqeks.png\" \/>)\u3002\u4e0d\u8fc7 Continuous-Time CT \u7684\u8bad\u7ec3\u7a33\u5b9a\u6027\u53c8\u66f4\u5dee&#xff0c;\u5b9e\u9a8c\u4e2d\u751a\u81f3\u9700\u8981\u4ece\u9884\u8bad\u7ec3 EDM \u521d\u59cb\u5316\u624d\u80fd\u7a33\u5b9a\u6bd4\u8f83\u3002<\/p>\n<p>\u8fd9\u7ec4\u7ed3\u679c\u8bf4\u660e Consistency Models \u5e76\u4e0d\u662f\u201c\u8fde\u7eed\u65f6\u95f4\u4e00\u5b9a\u6700\u597d\u201d\u6216\u8005\u201c\u79bb\u6563\u65f6\u95f4\u4e00\u5b9a\u6700\u597d\u201d&#xff0c;CD \u548c CT \u7684\u4f18\u5316\u6027\u8d28\u5b9e\u9645\u4e0a\u5e76\u4e0d\u76f8\u540c\u3002<\/p>\n<h4>5.6 Table 3&#xff1a;\u63a8\u7406\u867d\u7136\u5feb&#xff0c;\u4f46\u8bad\u7ec3\u672c\u8eab\u5e76\u4e0d\u4fbf\u5b9c<\/h4>\n<p><img loading=\"lazy\" decoding=\"async\" alt=\"\" height=\"510\" src=\"2026-08-27ia0eoqhftlm.png\" width=\"1293\" \/><\/p>\n<p>Table 3 \u7ed9\u51fa\u4e86\u5b8c\u6574\u8bad\u7ec3\u8d85\u53c2\u6570\u3002CIFAR-10 \u4f7f\u7528 8 \u5f20 GPU&#xff0c;\u800c ImageNet 64 \u00d7 64 \u548c LSUN 256 \u00d7 256 \u5b9e\u9a8c\u4f7f\u7528 64 \u5f20 GPU&#xff1b;\u8bad\u7ec3\u8fed\u4ee3\u6570\u4ece 600k \u5230 1000k \u4e0d\u7b49\u3002\u4f5c\u8005\u8fd8\u8bf4\u660e\u5b9e\u9a8c\u8fd0\u884c\u5728 Nvidia A100 GPU \u96c6\u7fa4\u4e0a\u3002<br \/>\n\u4ece\u5de5\u7a0b\u89d2\u5ea6\u770b&#xff0c;\u8fd9\u4e00\u70b9\u5f88\u503c\u5f97\u533a\u5206&#xff1a;<\/p>\n<p>Consistency Models \u89e3\u51b3\u7684\u662f Sampling Cost&#xff0c;\u800c\u4e0d\u662f\u8ba9\u6574\u4e2a\u751f\u6210\u6a21\u578b\u8bad\u7ec3\u8fc7\u7a0b\u7a81\u7136\u53d8\u5f97\u4fbf\u5b9c\u3002<\/p>\n<p>\u5c24\u5176 CD \u672c\u8eab\u9700\u8981\u9884\u8bad\u7ec3 EDM&#xff0c;\u800c\u5927\u89c4\u6a21 CT \u540c\u6837\u9700\u8981\u76f8\u5f53\u53ef\u89c2\u7684\u8bad\u7ec3\u8d44\u6e90\u3002\u56e0\u6b64\u201c\u4e00\u6b65\u751f\u6210\u201d\u8bf4\u7684\u662f\u63a8\u7406\u9636\u6bb5\u53ea\u9700\u8981\u4e00\u6b21\u7f51\u7edc\u8bc4\u4f30&#xff0c;\u5e76\u4e0d\u610f\u5473\u7740\u8bad\u7ec3\u6210\u672c\u4e5f\u53ea\u6709\u4f20\u7edf Diffusion \u7684\u51e0\u5341\u5206\u4e4b\u4e00\u3002<\/p>\n<hr \/>\n<h3>\u516d\u3001Zero-Shot \u7f16\u8f91\u4e0e\u603b\u7ed3&#xff1a;Consistency Models \u771f\u6b63\u6709\u610f\u601d\u7684\u5730\u65b9\u4e0d\u53ea\u662f\u201c\u4e00\u6b65\u751f\u6210\u201d<\/h3>\n<p>\u5982\u679c Consistency Models \u53ea\u662f\u628a Diffusion Model \u84b8\u998f\u6210\u4e00\u6b65\u7f51\u7edc&#xff0c;\u5b83\u672c\u8d28\u4e0a\u4ecd\u7136\u53ea\u662f\u53c8\u4e00\u79cd Acceleration \/ Distillation Method\u3002<\/p>\n<p>\u8fd9\u7bc7\u8bba\u6587\u771f\u6b63\u6709\u610f\u601d\u7684\u5730\u65b9&#xff0c;\u662f\u5b83\u867d\u7136\u53ef\u4ee5\u4e00\u6b65\u751f\u6210&#xff0c;\u5374\u6ca1\u6709\u5b8c\u5168\u727a\u7272 Diffusion Model \u90a3\u5957\u7075\u6d3b\u7684\u8fed\u4ee3\u5f0f\u63a8\u7406\u673a\u5236\u3002<\/p>\n<h4>6.1 Figure 6&#xff1a;\u6ca1\u6709\u4e3a\u7f16\u8f91\u4efb\u52a1\u8bad\u7ec3&#xff0c;\u5374\u53ef\u4ee5\u76f4\u63a5\u505a Colorization\u3001Super-Resolution \u548c SDEdit<\/h4>\n<p>\u8bba\u6587\u5728 LSUN Bedroom 256 \u00d7 256 \u4e0a\u4f7f\u7528 CD \u8bad\u7ec3 Consistency Model&#xff0c;\u7136\u540e\u76f4\u63a5\u8fdb\u884c Zero-Shot Image Editing\u3002<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" alt=\"\" height=\"615\" src=\"2026-08-27klf2ewlmf2c.png\" width=\"1281\" \/><\/p>\n<p>\u8bba\u6587 Figure 6&#xff1a;Consistency Model \u7684 Zero-Shot \u56fe\u50cf\u7f16\u8f91\u7ed3\u679c<\/p>\n<p>Figure 6a \u8f93\u5165 Gray-Scale Image&#xff0c;\u6a21\u578b\u76f4\u63a5\u751f\u6210\u591a\u4e2a\u5408\u7406\u7684\u5f69\u8272\u7248\u672c&#xff1b;Figure 6b \u4ece 32 \u00d7 32 Low-Resolution Image \u6062\u590d\u5230 256 \u00d7 256&#xff1b;Figure 6c \u8f93\u5165\u4eba\u5de5\u7ed8\u5236\u7684 Stroke&#xff0c;\u6a21\u578b\u5219\u5b8c\u6210\u7c7b\u4f3c SDEdit \u7684 Stroke-Guided Generation\u3002<\/p>\n<p>\u5173\u952e\u5728\u4e8e&#xff1a;\u8fd9\u4e2a\u6a21\u578b\u4ece\u6765\u6ca1\u6709\u9488\u5bf9 Colorization\u3001Super-Resolution \u6216 Stroke Input \u4e13\u95e8\u8bad\u7ec3\u3002<\/p>\n<p>\u8fd9\u4e9b\u4efb\u52a1\u4e3b\u8981\u901a\u8fc7\u4fee\u6539 Multistep Sampling \u5b9e\u73b0\u3002\u6838\u5fc3\u64cd\u4f5c\u662f\u5728\u6bcf\u4e00\u6b21 Consistency Denoising \u540e&#xff0c;\u5c06\u5df2\u77e5\u6761\u4ef6\u91cd\u65b0\u5199\u56de\u6837\u672c&#xff0c;\u518d\u52a0\u5165\u566a\u58f0\u8fdb\u5165\u4e0b\u4e00\u6b65\u3002<\/p>\n<p>Algorithm 4 \u5c06\u8fd9\u4e00\u8fc7\u7a0b\u7edf\u4e00\u6210\u4e00\u4e2a\u7ebf\u6027\u53d8\u6362 (A) \u548c Mask (\\\\Omega) \u7684\u6846\u67b6&#xff1a;Inpainting \u4e2d (A) \u53ef\u4ee5\u76f4\u63a5\u53d6 Identity&#xff1b;Colorization \u548c Super-Resolution \u5219\u628a\u5df2\u77e5\u4fe1\u606f\u53d8\u6362\u5230\u4e00\u4e2a\u66f4\u5bb9\u6613 Mask \u7684\u7a7a\u95f4&#xff0c;\u518d\u5728\u6bcf\u4e00\u6b65\u751f\u6210\u540e\u91cd\u65b0\u6ce8\u5165\u3002<br \/>\nAppendix \u4e2d\u7684 Figure 8&#xff5e;13 \u8fdb\u4e00\u6b65\u7ed9\u51fa\u4e86 Colorization\u3001Super-Resolution\u3001Inpainting\u3001Interpolation\u3001Denoising \u548c Stroke-Guided Generation \u7684\u66f4\u591a\u7ed3\u679c\u3002\u7279\u522b\u662f Denoising \u66f4\u76f4\u63a5&#xff1a;\u5982\u679c\u56fe\u50cf\u88ab\u65b9\u5dee\u4e3a (<img decoding=\"async\" alt=\"\\\\sigma^2\" class=\"mathcode\" src=\"2026-08-27jxjwujoyc40.png\" \/>) \u7684 Gaussian Noise \u6c61\u67d3&#xff0c;\u53ea\u8981 (<img decoding=\"async\" alt=\"\\\\sigma\\\\in[\\\\epsilon,T]\" class=\"mathcode\" src=\"2026-08-27jtdu5jp5lc1.png\" \/>)&#xff0c;\u76f4\u63a5\u8c03\u7528 (<img decoding=\"async\" alt=\"f_\\\\theta(x,\\\\sigma)\" class=\"mathcode\" src=\"2026-08-27mnokejv2bzn.png\" \/>) \u5c31\u80fd\u8fdb\u884c\u4e00\u6b65\u53bb\u566a\u3002<br \/>\nFigure 14&#xff5e;21 \u5219\u8865\u5145\u5c55\u793a\u4e86 CD \u548c CT \u5728 CIFAR-10\u3001ImageNet\u3001LSUN Bedroom\u3001LSUN Cat \u4e0a\u7684\u4e00\u6b65\u4e0e\u4e24\u6b65\u6837\u672c\u3002\u5176\u4e2d CD \u4ece\u4e00\u6b65\u589e\u52a0\u5230\u4e24\u6b65\u540e&#xff0c;CIFAR-10 FID \u4ece 3.55 \u964d\u5230 2.93&#xff0c;ImageNet \u4ece 6.20 \u964d\u5230 4.70&#xff0c;Bedroom \u4ece 7.80 \u964d\u5230 5.22&#xff0c;Cat \u4ece 10.99 \u964d\u5230 8.84&#xff1b;CT \u540c\u6837\u8868\u73b0\u51fa\u660e\u663e\u7684\u591a\u6b65\u8d28\u91cf\u63d0\u5347\u3002<\/p>\n<h4>6.2 \u5982\u679c\u628a\u8fd9\u7bc7\u8bba\u6587\u538b\u7f29\u6210\u4e00\u53e5\u8bdd<\/h4>\n<p>Consistency Models \u7684\u6838\u5fc3\u5e76\u4e0d\u662f&#xff1a;<\/p>\n<p>\u201c\u8bad\u7ec3\u4e00\u4e2a\u7f51\u7edc\u76f4\u63a5\u628a Noise \u53d8\u6210 Image\u3002\u201d<\/p>\n<p>\u771f\u6b63\u5173\u952e\u7684\u662f&#xff1a;<\/p>\n<p>\u628a PF ODE \u4e0a\u201c\u540c\u4e00\u6761\u8f68\u8ff9\u7684\u6240\u6709\u4f4d\u7f6e\u5e94\u8be5\u5bf9\u5e94\u540c\u4e00\u4e2a\u6570\u636e\u7aef\u70b9\u201d\u8fd9\u4e00 Self-Consistency \u5173\u7cfb\u53d8\u6210\u5b66\u4e60\u76ee\u6807&#xff0c;\u4ece\u800c\u8ba9\u539f\u672c\u9700\u8981\u6570\u503c\u79ef\u5206\u9010\u6b65\u6c42\u89e3\u7684\u751f\u6210\u8fc7\u7a0b&#xff0c;\u53ef\u4ee5\u76f4\u63a5\u5b66\u4e60\u6210\u4e00\u4e2a\u5168\u5c40\u6620\u5c04\u3002<\/p>\n<p>\u524d\u8005\u89e3\u51b3 Diffusion Acceleration&#xff0c;\u540e\u8005\u5219\u8bd5\u56fe\u628a Consistency Model \u4ece\u201c\u84b8\u998f\u65b9\u6cd5\u201d\u63d0\u5347\u6210\u201c\u4e00\u7c7b\u65b0\u7684\u751f\u6210\u6a21\u578b\u201d\u3002<\/p>\n<h4>6.3 \u6700\u540e\u5e94\u8be5\u8bb0\u4f4f\u4ec0\u4e48&#xff1f;<\/h4>\n<p>\u8fd9\u7bc7\u8bba\u6587\u6700\u503c\u5f97\u8bb0\u4f4f\u7684&#xff0c;\u6211\u8ba4\u4e3a\u6709\u56db\u70b9\u3002<\/p>\n<p>\u7b2c\u4e00&#xff0c;\u5b83\u6539\u53d8\u4e86\u5feb\u901f\u6269\u6563\u751f\u6210\u7684\u5efa\u6a21\u89c6\u89d2\u3002 \u8fc7\u53bb\u5f88\u591a\u65b9\u6cd5\u662f\u5728\u7814\u7a76\u600e\u6837\u628a 1000 \u6b65\u53d8\u6210 100 \u6b65\u300120 \u6b65\u300110 \u6b65&#xff1b;Consistency Model \u5219\u76f4\u63a5\u95ee&#xff1a;\u5982\u679c\u6700\u7ec8\u76ee\u6807\u59cb\u7ec8\u662f\u8f68\u8ff9\u7684\u6570\u636e\u7aef\u70b9&#xff0c;\u4e3a\u4ec0\u4e48\u4e0d\u76f4\u63a5\u5b66\u4e60\u8fd9\u4e2a\u6620\u5c04&#xff1f;<\/p>\n<p>\u7b2c\u4e8c&#xff0c;Self-Consistency \u662f\u6574\u4e2a\u65b9\u6cd5\u7684\u6838\u5fc3\u3002 \u540c\u4e00\u6761 PF ODE \u8f68\u8ff9\u4e0a\u7684\u4e0d\u540c\u566a\u58f0\u72b6\u6001\u5fc5\u987b\u9884\u6d4b\u540c\u4e00\u4e2a\u7ed3\u679c&#xff0c;\u4e00\u6b65\u751f\u6210\u53ea\u662f\u8fd9\u4e2a\u6027\u8d28\u4ea7\u751f\u7684\u81ea\u7136\u7ed3\u679c&#xff0c;\u800c\u4e0d\u662f\u4eba\u4e3a\u89c4\u5b9a\u201c\u7f51\u7edc\u53ea\u80fd\u8dd1\u4e00\u6b65\u201d\u3002<\/p>\n<p>\u7b2c\u4e09&#xff0c;\u4e00\u6b65\u751f\u6210\u4e0e\u8fed\u4ee3\u751f\u6210\u5e76\u4e0d\u77db\u76fe\u3002 Consistency Model \u53ef\u4ee5\u4e00\u6b21\u7f51\u7edc\u8c03\u7528\u76f4\u63a5\u751f\u6210&#xff0c;\u540c\u65f6\u4e5f\u5141\u8bb8\u91cd\u65b0\u52a0\u566a\u540e\u7ee7\u7eed\u8c03\u7528\u6a21\u578b&#xff0c;\u7528\u989d\u5916\u8ba1\u7b97\u63d0\u5347\u8d28\u91cf\u3002\u8fd9\u4f7f\u5b83\u4fdd\u7559\u4e86 Diffusion Model \u5f88\u91cd\u8981\u7684 Compute-Quality Trade-off \u548c Zero-Shot Editing \u80fd\u529b\u3002\u8bba\u6587\u6700\u7ec8\u4e5f\u5728 Inpainting\u3001Colorization\u3001Super-Resolution\u3001Denoising\u3001Interpolation \u548c Stroke-Guided Generation \u4e0a\u5c55\u793a\u4e86\u8fd9\u4e00\u70b9\u3002<\/p>\n<p>\u7b2c\u56db&#xff0c;CD \u548c CT \u7684\u610f\u4e49\u4e0d\u540c\u3002 CD \u5728\u672c\u6587\u4e2d\u5df2\u7ecf\u5c55\u793a\u51fa\u975e\u5e38\u5f3a\u7684\u4e00\u6b65\/\u5c11\u6b65\u84b8\u998f\u6027\u80fd&#xff0c;\u4f8b\u5982 CIFAR-10 \u4e00\u6b65 FID &#061; 3.55\u3001ImageNet 64 \u00d7 64 \u4e00\u6b65 FID &#061; 6.20&#xff1b;CT \u7684\u7edd\u5bf9\u8d28\u91cf\u8fd8\u660e\u663e\u5f31\u4e8e\u6700\u5f3a GAN \u548c\u591a\u6b65 Diffusion&#xff0c;\u4f46\u5b83\u8bc1\u660e\u4e86\u4e00\u4ef6\u66f4\u57fa\u7840\u7684\u4e8b\u60c5\u2014\u2014Consistency Model \u5e76\u4e0d\u5fc5\u987b\u4f9d\u9644\u4e8e Diffusion Teacher&#xff0c;\u5b83\u53ef\u4ee5\u76f4\u63a5\u4ece\u6570\u636e\u8bad\u7ec3&#xff0c;\u4f5c\u4e3a\u72ec\u7acb\u7684 Generative Model \u5b58\u5728\u3002<\/p>\n<p>\u4ece\u65b9\u6cd5\u8bbe\u5b9a\u4e0a\u770b&#xff0c;\u8bba\u6587\u4ecd\u7136\u7559\u4e0b\u4e86\u4e00\u4e9b\u660e\u663e\u7a7a\u95f4&#xff1a;\u591a\u6b65\u91c7\u6837\u65f6\u95f4\u70b9\u76ee\u524d\u901a\u8fc7 Greedy &#043; Ternary Search \u9009\u62e9&#xff1b;Continuous-Time Objective \u5b58\u5728\u8f83\u5927\u7684\u8bad\u7ec3\u65b9\u5dee\u548c Forward-Mode Automatic Differentiation \u4f9d\u8d56&#xff1b;\u800c\u5927\u89c4\u6a21\u8bad\u7ec3\u672c\u8eab\u4f9d\u65e7\u9700\u8981\u76f8\u5f53\u53ef\u89c2\u7684\u8ba1\u7b97\u8d44\u6e90\u3002<br \/>\n\u4f46\u5b83\u63d0\u51fa\u7684\u6838\u5fc3\u95ee\u9898\u975e\u5e38\u6709\u542f\u53d1\u6027&#xff1a;<\/p>\n<p>\u751f\u6210\u6a21\u578b\u771f\u7684\u5fc5\u987b\u5b8c\u6574\u6a21\u62df\u4e00\u6761\u4ece Noise \u5230 Data \u7684\u8f68\u8ff9\u5417&#xff1f;\u8fd8\u662f\u53ea\u8981\u5b66\u4f1a\u8fd9\u6761\u8f68\u8ff9\u4e0a\u6240\u6709\u72b6\u6001\u6700\u7ec8\u5e94\u8be5\u201c\u4fdd\u6301\u4e00\u81f4\u5730\u6307\u5411\u54ea\u91cc\u201d\u5c31\u591f\u4e86&#xff1f;<\/p>\n<p>Consistency Models \u7ed9\u51fa\u7684\u7b54\u6848\u662f\u540e\u8005\u3002<\/p>\n<p>\u800c\u8fd9&#xff0c;\u4e5f\u6b63\u662f\u8fd9\u7bc7\u8bba\u6587\u6700\u503c\u5f97\u8bb0\u4f4f\u7684\u5730\u65b9\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u8bba\u6587\u9898\u76ee&#xff1a; Consistency Models&#xff08;\u4e00\u81f4\u6027\u6a21\u578b&#xff09;<br \/>\n\u4f1a\u8bae&#xff1a; ICML 2023\u6458\u8981&#xff1a; \u6269\u6563\u6a21\u578b\u6781\u5927\u63a8\u52a8\u4e86\u56fe\u50cf\u3001\u97f3\u9891\u548c\u89c6\u9891\u751f\u6210\u7684\u53d1\u5c55&#xff0c;\u4f46\u5b83\u4eec\u4f9d\u8d56\u8fed\u4ee3\u5f0f\u91c7\u6837\u8fc7\u7a0b&#xff0c;\u56e0\u6b64\u751f\u6210\u901f\u5ea6\u8f83\u6162\u3002\u4e3a\u89e3\u51b3\u8fd9\u4e00\u9650\u5236&#xff0c;\u672c\u6587\u63d0\u51fa Consistency Models&#xff08;\u4e00\u81f4\u6027\u6a21\u578b&#xff09;&#xff0c;\u4e00\u79cd\u80fd\u591f\u5c06\u566a\u58f0\u76f4\u63a5\u6620\u5c04\u5230\u6570\u636e\u7684\u65b0\u578b\u751f\u6210\u6a21\u578b\u3002Consiste<\/p>\n","protected":false},"author":2,"featured_media":96033,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[50,2520,86,523],"topic":[],"class_list":["post-96053","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-server","tag-50","tag-2520","tag-86","tag-523"],"yoast_head":"<!-- This site is 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Models&#xff08;\u4e00\u81f4\u6027\u6a21\u578b&#xff09; \u4f1a\u8bae&#xff1a; ICML 2023\u6458\u8981&#xff1a; \u6269\u6563\u6a21\u578b\u6781\u5927\u63a8\u52a8\u4e86\u56fe\u50cf\u3001\u97f3\u9891\u548c\u89c6\u9891\u751f\u6210\u7684\u53d1\u5c55&#xff0c;\u4f46\u5b83\u4eec\u4f9d\u8d56\u8fed\u4ee3\u5f0f\u91c7\u6837\u8fc7\u7a0b&#xff0c;\u56e0\u6b64\u751f\u6210\u901f\u5ea6\u8f83\u6162\u3002\u4e3a\u89e3\u51b3\u8fd9\u4e00\u9650\u5236&#xff0c;\u672c\u6587\u63d0\u51fa Consistency Models&#xff08;\u4e00\u81f4\u6027\u6a21\u578b&#xff09;&#xff0c;\u4e00\u79cd\u80fd\u591f\u5c06\u566a\u58f0\u76f4\u63a5\u6620\u5c04\u5230\u6570\u636e\u7684\u65b0\u578b\u751f\u6210\u6a21\u578b\u3002Consiste\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.wsisp.com\/helps\/96053.html\" \/>\n<meta property=\"og:site_name\" content=\"\u7f51\u7855\u4e92\u8054\u5e2e\u52a9\u4e2d\u5fc3\" \/>\n<meta property=\"article:published_time\" content=\"2026-08-27T03:02:43+00:00\" \/>\n<meta property=\"og:image\" 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