{"id":121148,"date":"2026-11-02T04:25:16","date_gmt":"2026-11-01T20:25:16","guid":{"rendered":"https:\/\/www.wsisp.com\/helps\/121148.html"},"modified":"2026-11-02T04:25:16","modified_gmt":"2026-11-01T20:25:16","slug":"neurips-2026-%e6%96%b0%e5%8a%a0%e5%9d%a1%e5%9b%bd%e7%ab%8b-fuseadapt%ef%bc%9a%e8%ae%a9%e5%a4%9a%e6%a8%a1%e6%80%81%e8%9e%8d%e5%90%88%e5%ad%a6%e4%bc%9a%e9%a2%84%e6%b5%8b%e7%bc%ba%e5%a4%b1%e4%bf%a1","status":"publish","type":"post","link":"https:\/\/www.wsisp.com\/helps\/121148.html","title":{"rendered":"NeurIPS 2026 | \u65b0\u52a0\u5761\u56fd\u7acb FuseAdapt\uff1a\u8ba9\u591a\u6a21\u6001\u878d\u5408\u5b66\u4f1a\u9884\u6d4b\u7f3a\u5931\u4fe1\u606f"},"content":{"rendered":"<p>\u4f20\u611f\u5668\u7f3a\u5e2d&#xff0c;\u5206\u5272\u5982\u4f55\u7ee7\u7eed&#xff1f;\u65b0\u52a0\u5761\u56fd\u7acb FuseAdapt&#xff1a;\u5728\u51bb\u7ed3\u9aa8\u5e72\u7684\u9002\u914d\u8def\u5f84\u4e2d\u878d\u5408\u591a\u6a21\u6001<\/p>\n<p>unsetunset1. \u4e00\u53e5\u8bdd\u603b\u7ed3unsetunset<\/p>\n<p>FuseAdapt \u9762\u5411\u7f3a\u5931\u6a21\u6001\u7684\u8bed\u4e49\u5206\u5272&#xff0c;\u5728\u51bb\u7ed3\u9aa8\u5e72\u5185\u4ea4\u6362\u4f4e\u79e9\u6b8b\u5dee\u4fe1\u606f&#xff0c;\u5e76\u7528\u7f3a\u5931\u6a21\u6001\u8868\u5f81\u9884\u6d4b\u589e\u5f3a\u9c81\u68d2\u6027\u3002\u5728 MCubeS \u7684\u5168\u90e8\u975e\u7a7a\u6a21\u6001\u7ec4\u5408\u4e0a&#xff0c;\u5e73\u5747 mIoU \u8fbe\u5230 52.89\u3002<\/p>\n<p><img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/11\/20261101202510-6ae7a026aa985.webp\" alt=\"\u56fe\u7247\" \/><\/p>\n<p>unsetunset2. \u8bba\u6587\u4fe1\u606funsetunset<\/p>\n<ul>\n<li>\n<p>\u9898\u76ee&#xff1a; FuseAdapt: Parameter-Efficient Multimodal Fusion for Semantic Segmentation with Missing Modalities | FuseAdapt&#xff1a;\u9762\u5411\u7f3a\u5931\u6a21\u6001\u8bed\u4e49\u5206\u5272\u7684\u53c2\u6570\u9ad8\u6548\u591a\u6a21\u6001\u878d\u5408<\/p>\n<\/li>\n<li>\n<p>\u53d1\u8868&#xff1a;NeurIPS 2026<\/p>\n<\/li>\n<li>\n<p>\u4f5c\u8005&#xff1a; Xin Zhang\u3001Robby T. Tan<\/p>\n<\/li>\n<li>\n<p>\u5355\u4f4d&#xff1a; \u65b0\u52a0\u5761\u56fd\u7acb\u5927\u5b66<\/p>\n<\/li>\n<li>\n<p>\u9879\u76ee\u4e3b\u9875&#xff1a;<\/p>\n<\/li>\n<li>\n<p>https:\/\/devinxzhang.github.io\/FuseAdapt-Page\/<\/p>\n<\/li>\n<\/ul>\n<p>unsetunset3. \u8bba\u6587\u6458\u8981unsetunset<\/p>\n<p>\u591a\u4e2a\u4f20\u611f\u5668\u53ef\u4ee5\u63d0\u4f9b\u4e92\u8865\u7684\u4fe1\u606f&#xff0c;\u4f46\u662f\u72ec\u7acb\u7684\u7f16\u7801\u5668\u4f1a\u5e26\u6765\u8f83\u9ad8\u7684\u6210\u672c&#xff0c;\u800c\u5171\u4eab\u7f16\u7801\u5668\u53c8\u5bb9\u6613\u504f\u5411\u4e8e\u5f3a\u52bf\u6a21\u5f0f\u3002FuseAdapt \u5c06\u878d\u5408\u9650\u5236\u5728\u51bb\u7ed3\u89c6\u89c9\u57fa\u7840\u6a21\u578b\u7684\u9002\u914d\u8def\u5f84\u91cc&#xff0c;\u5e76\u4e14\u5229\u7528\u5bf9\u88ab\u906e\u63a9\u6a21\u5f0f\u6f5c\u5728\u8868\u793a\u7684\u5b66\u4e60\u6765\u5b66\u4e60\u8de8\u6a21\u6001\u5197\u4f59&#xff0c;\u5728\u4e09\u4e2a\u57fa\u51c6\u4e0a\u63d0\u9ad8\u4e86\u5b8c\u6574\u548c\u7f3a\u5931\u6a21\u5f0f\u6761\u4ef6\u4e0b\u5206\u5272\u7684\u6548\u679c\u3002<\/p>\n<p>unsetunset4. \u4e3b\u8981\u521b\u65b0\u4e4b\u5904unsetunset<\/p>\n<p>\u521b\u65b0\u70b9 1&#xff1a;\u79c1\u6709\u7684\u6ce8\u610f\u529b\u9002\u914d\u3001\u8de8\u6a21\u6001\u6b8b\u5dee\u901a\u4fe1<\/p>\n<p>\u67e5\u8be2\u4e0e\u503c\u6295\u5f71\u7684\u4f4e\u79e9\u9002\u914d\u4fdd\u6301\u6a21\u6001\u79c1\u6709&#xff0c;\u5728\u524d\u9988\u7f51\u7edc\u4f4e\u79e9\u6b8b\u5dee\u6fc0\u6d3b\u4e4b\u95f4\u4f20\u9012\u4fe1\u606f&#xff0c;\u5e76\u4e14\u6309\u7167\u53ef\u7528\u4f20\u611f\u5668\u7684\u60c5\u51b5\u5bf9\u8def\u7531\u8fdb\u884c\u5f52\u4e00\u5316\u3002<\/p>\n<p>\u521b\u65b0\u70b9 2&#xff1a;\u5bf9\u67d0\u4e2a\u7f3a\u5931\u6a21\u6001\u8fdb\u884c\u9884\u6d4b<\/p>\n<p>\u9884\u6d4b\u5f0f\u6a21\u6001\u5efa\u6a21(Predictive Modality Modeling, PMM)\u53ef\u4ee5\u5bf9\u6307\u5b9a\u7684\u7f3a\u5931\u4f20\u611f\u5668\u505a\u51fa\u9884\u6d4b&#xff0c;\u5e76\u4e14\u7ed9\u51fa\u5177\u4f53\u7684\u8bad\u7ec3\u76ee\u6807&#xff0c;\u800c\u4e00\u822c\u7684\u8f93\u51fa\u6216\u8005\u7279\u5f81\u878d\u5408\u5219\u6ca1\u6709\u8fd9\u4e48\u660e\u786e\u3002<\/p>\n<p>\u521b\u65b0\u70b9 3&#xff1a;\u901a\u8fc7\u63a7\u5236\u5b9e\u9a8c\u6765\u9a8c\u8bc1\u8bbe\u8ba1\u65b9\u6848\u53ca\u5176\u8fb9\u754c<\/p>\n<p>\u4e09\u4e2a\u57fa\u51c6\u4ee5\u53ca\u548c\u9aa8\u5e72\u3001\u540c\u8bad\u7ec3\u8bbe\u7f6e\u76f8\u6bd4\u8f83\u7684\u7ed3\u679c\u90fd\u652f\u6301\u4e86\u8be5\u8bbe\u8ba1\u65b9\u6848&#xff1b;\u8bba\u6587\u8fd8\u63d0\u5230\u90e8\u7f72\u7684\u6210\u672c\u4ee5\u53ca\u5b83\u7684\u8106\u5f31\u6027\u3002<\/p>\n<p>unsetunset5. \u65b9\u6cd5\u8be6\u89e3unsetunset<\/p>\n<p>5.1 \u95ee\u9898\u7684\u754c\u5b9a\u4ee5\u53ca\u6574\u4e2a\u4f53\u7cfb\u7684\u5927\u81f4\u7ed3\u6784<\/p>\n<p>\u5bf9\u4e8e\u540c\u4e00\u4e2a\u573a\u666f\u4e0b\u7684\u591a\u6a21\u6001\u6570\u636e\u8fdb\u884c\u5904\u7406&#xff0c;\u5e76\u4e14\u5f97\u5230\u7684\u662f\u6bcf\u4e00\u50cf\u7d20\u5bf9\u5e94\u7684\u7c7b\u522b\u3002\u8bba\u6587\u628a\u6a21\u6001\u5b8c\u6574\u8bed\u4e49\u5206\u5272&#xff08;Modality-Complete Semantic Segmentation&#xff0c;MCSS&#xff09;\u53eb\u505a\u6a21\u6001\u5b8c\u6574\u8bed\u4e49\u5206\u5272&#xff0c;\u628a\u6a21\u6001\u4e0d\u5b8c\u6574\u8bed\u4e49\u5206\u5272&#xff08;Modality-Incomplete Semantic Segmentation&#xff0c;MISS&#xff09;\u53eb\u505a\u6a21\u6001\u4e0d\u5b8c\u6574\u8bed\u4e49\u5206\u5272\u3002\u5404\u4e2a\u6a21\u6001\u90fd\u4f7f\u7528\u4e00\u4e2a\u56fa\u5b9a\u7684\u89c6\u89c9\u57fa\u7840\u6a21\u578b&#xff08;Vision Foundation Model&#xff0c;VFM&#xff09;\u6765\u5b8c\u6210\u9002\u5e94\u548c\u4ea4\u4e92\u7684\u8fc7\u7a0b&#xff0c;\u5728\u6b64\u4e4b\u540e\u518d\u628a\u6240\u6709\u6a21\u6001\u5171\u4eab\u7684\u53ef\u89c1\u7279\u5f81\u9001\u5165\u4e00\u4e2a\u5171\u540c\u7684\u5206\u5272\u89e3\u7801\u5668\u4e2d\u53bb\u3002<\/p>\n<p><img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/11\/20261101202510-6ae7a026f29cd.png\" alt=\"\u56fe\u7247\" \/><\/p>\n<p>\u56fe1.&#xff1a; \u591a\u6a21\u6001\u878d\u5408\u7b56\u7565\u6bd4\u8f83\u548cMCubeS\u4e0a\u5404\u79cd\u6a21\u5f0f\u7ec4\u5408\u540e\u7684MCSS\u7ed3\u679c\u3002<\/p>\n<p><img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/11\/20261101202511-6ae7a02726b22.png\" alt=\"\u56fe\u7247\" \/><\/p>\n<p>\u56fe2.&#xff1a; \u7f3a\u5931\u6a21\u6001\u9c81\u68d2\u6027\u7b56\u7565\u4e09\u79cd\u65b9\u6cd5\u7684\u6bd4\u8f83&#xff1a;\u8bed\u4e49\u951a\u70b9\u3001\u8bed\u4e49\u4e00\u81f4\u6027\u548cPMM&#xff1b;\u53f3\u8fb9\u4e3aDELIVER\u548cMUSES\u7684\u7ed3\u679c\u3002<\/p>\n<p><img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/11\/20261101202511-6ae7a0274f07c.png\" alt=\"\u56fe\u7247\" \/><\/p>\n<p>\u56fe3.&#xff1a; FuseAdapt \u6574\u4f53\u7ed3\u6784\u5305\u62ec\u51bb\u7ed3\u9aa8\u5e72\u4e2d\u9002\u914d\u7a7a\u95f4\u7684\u878d\u5408\u548c\u6559\u5e08\u6307\u5bfc\u4e0b\u7684\u7f3a\u5931\u6a21\u6001\u9884\u6d4b\u3002<\/p>\n<p>5.2 \u79c1\u6709\u6ce8\u610f\u529b\u9002\u914d<\/p>\n<p>\u4f4e\u79e9\u9002\u914d&#xff08;Low-Rank Adaptation&#xff0c;LoRA&#xff09;\u53ea\u5bf9\u67e5\u8be2\u3001\u503c\u6295\u5f71\u8fdb\u884c\u66f4\u65b0&#xff0c;\u800c\u5404\u4e2a\u4f20\u611f\u5668\u5404\u81ea\u7684\u4fee\u6b63\u65b9\u5411\u662f\u56fa\u5b9a\u7684&#xff0c;\u952e\u548c\u8f93\u51fa\u6295\u5f71\u5219\u662f\u5171\u4eab\u7684\u3002<\/p>\n<p>\u5176\u4e2d\u8868\u793a\u6a21\u6001&#xff0c;\u662f\u8f93\u5165\u7279\u5f81\u5411\u91cf&#xff0c;\u662f\u8bcd\u5143\u7684\u6570\u91cf&#xff0c;\u662f\u9690\u85cf\u5c42\u7684\u7ef4\u5ea6&#xff1b;\u662f\u56fa\u5b9a\u53c2\u6570&#xff0c;\u662f\u67e5\u8be2\u548c\u503c&#xff1b;\u3001\u662f\u53ef\u4ee5\u5b66\u4e60\u5230\u7684\u53c2\u6570&#xff0c;\u4e14\u3002<\/p>\n<p>\u516c\u5f0f\u89e3\u8bfb&#xff1a; \u901a\u8fc7\u4e24\u4e2a\u5c0f\u77e9\u9635\u76f8\u4e58\u6765\u4fee\u6b63\u9884\u8bad\u7ec3\u6295\u5f71&#xff0c;\u5e76\u4e14\u53bb\u5b66\u4e60\u4f20\u611f\u5668\u4e4b\u95f4\u7684\u5dee\u522b&#xff0c;\u5728\u6b64\u8fc7\u7a0b\u4e2d\u53c8\u5bf9\u8bad\u7ec3\u53c2\u6570\u7684\u6570\u91cf\u52a0\u4ee5\u9650\u5236\u3002<\/p>\n<p>5.3 \u524d\u9988\u4f4e\u79e9\u6b8b\u5dee\u8def\u7531<\/p>\n<p>\u524d\u9988\u7f51\u7edc&#xff08;Feed-Forward Network&#xff0c;FFN&#xff09;\u53ea\u4f20\u9012\u4f4e\u79e9\u6b8b\u5dee\u6fc0\u6d3b&#xff0c;\u56fa\u5b9a\u7684\u7a20\u5bc6\u53d8\u6362\u4ecd\u7136\u5bf9\u63a5\u6536\u6a21\u6001\u672c\u8eab\u8d77\u4f5c\u7528\u3002<\/p>\n<p>\u662f\u975e\u7a7a\u53ef\u89c1\u6a21\u6001\u96c6&#xff0c;\u662f\u8bcd\u5143\u7684\u4f4d\u7f6e&#xff0c;\u662f\u6765\u6e90\u6a21\u6001&#xff0c;\u662f\u63a5\u6536\u6a21\u6001\u7684\u8def\u7531\u5668&#xff0c;\u662f\u6743\u91cd\u3002<\/p>\n<p>\u516c\u5f0f\u89e3\u8bfb&#xff1a; \u9996\u5148\u6392\u9664\u6389\u6ca1\u6709\u6765\u6e90\u7684\u90e8\u5206&#xff0c;\u7136\u540e\u628a\u53ef\u4ee5\u770b\u89c1\u7684\u90e8\u5206\u8fdb\u884c\u5f52\u4e00\u5316\u5904\u7406&#xff1b;\u6bcf\u4e00\u4e2a\u5730\u65b9\u90fd\u53ef\u4ee5\u7528\u4e0d\u540c\u7684\u878d\u5408\u7cfb\u6570\u6765\u8868\u793a\u3002<\/p>\n<p>\u5176\u4e2d\u662f\u51bb\u7ed3\u7684FFN\u6743\u91cd&#xff0c;\u662f\u4ece\u6e90\u6a21\u6001\u5f97\u5230\u7684\u4f4e\u79e9\u66f4\u65b0&#xff1b;\u662f\u4e2d\u95f4\u548c\u8f93\u51fa\u7279\u5f81&#xff0c;\u662f\u6fc0\u6d3b\u51fd\u6570&#xff0c;\u628a\u8bcd\u5143\u6743\u91cd\u5e7f\u64ad\u5230\u901a\u9053\u4e0a\u3002<\/p>\n<p>\u516c\u5f0f\u89e3\u8bfb&#xff1a; \u63a5\u6536\u6d41\u4fdd\u7559\u81ea\u5df1\u7a20\u5bc6\u7684\u8ba1\u7b97&#xff0c;\u5e76\u4e14\u52a0\u4e0a\u5176\u4ed6\u7684\u53ef\u89c1\u6a21\u5f0f\u7684\u6b8b\u5dee\u4fe1\u606f\u3002\u8def\u7531\u548c\u5e73\u5747\u4e00\u8d77\u6295\u5c04\u7f51\u683c&#xff0c;\u4e0d\u652f\u6301\u4efb\u4f55\u539f\u59cb\u8bcd\u5143\u957f\u5ea6\u3002<\/p>\n<p>5.4 PMM&#xff1a;\u6839\u636e\u53ef\u89c2\u5bdf\u5230\u7684\u7ebf\u7d22\u6765\u63a8\u65ad\u51fa\u7f3a\u5931\u8868\u5f81<\/p>\n<p>\u7ecf\u8fc7\u5145\u5206\u7684\u9884\u70ed\u4e4b\u540e&#xff0c;\u8bad\u7ec3\u4f1a\u4ee5\u4e00\u534a\u6982\u7387\u4fdd\u7559\u6240\u6709\u7684\u6a21\u6001\u4fe1\u606f&#xff0c;\u53e6\u5916\u4e00\u534a\u6982\u7387\u5219\u4f1a\u968f\u673a\u5730\u53bb\u6389\u4e00\u90e8\u5206&#xff0c;\u5e76\u4e14\u4fdd\u8bc1\u81f3\u5c11\u6709\u4e00\u4e2a\u6a21\u6001\u662f\u53ef\u89c1\u7684\u3002\u4ece\u88ab\u79fb\u9664\u7684\u6a21\u6001\u4e2d\u9009\u62e9\u76ee\u6807&#xff0c;\u4f7f\u7528\u6307\u6570\u79fb\u52a8\u5e73\u5747&#xff08;Exponential Moving Average&#xff0c;EMA&#xff09;\u4f5c\u4e3a\u6559\u5e08\u6765\u7ed9\u51fa\u5b8c\u6574\u7684\u4e0a\u4e0b\u6587\u8868\u793a\u3002<\/p>\n<p>\u5176\u4e2d\u4e3a\u76ee\u6807\u6a21\u6001\u3001\u662f\u5b83\u7684\u53ef\u5b66\u4e60\u67e5\u8be2\u3001\u662f\u53ef\u89c1\u7279\u5f81\u7684\u5747\u503c\u3001\u662f\u9884\u6d4b\u5668\u3001\u662f\u9884\u6d4b\u8868\u793a&#xff1b;\u5206\u522b\u662f\u5b66\u751f\u548c\u6559\u5e08\u7684\u9002\u914d\u53c2\u6570\u3001\u662f\u5e73\u6ed1\u7cfb\u6570\u3002<\/p>\n<p>\u516c\u5f0f\u89e3\u8bfb&#xff1a; \u67e5\u8be2\u6240\u6709\u53ef\u67e5\u770b\u7684\u4f4d\u7f6e\u6765\u5bfb\u627e\u7ebf\u7d22&#xff0c;\u4e0d\u8981\u53ea\u5728\u4e00\u4e2a\u5730\u65b9\u53cd\u590d\u67e5\u627e&#xff1b;\u8001\u5e08\u53ea\u4fdd\u7559\u9002\u5408\u5206\u652f\u7684EMA\u526f\u672c&#xff0c;\u5e76\u4e14\u5171\u4eab\u51bb\u7ed3\u7684\u4e3b\u5e72\u3002<\/p>\n<p>5.5 \u635f\u5931\u51fd\u6570<\/p>\n<p>\u662f\u6559\u5e08\u7684\u76ee\u6807\u8bcd\u5143&#xff0c;\u662f\u4f59\u5f26\u76f8\u4f3c\u5ea6&#xff0c;\u8868\u793a\u505c\u6b62\u68af\u5ea6&#xff1b;\u662f\u7c7b\u522b\u5e73\u8861\u7684\u5728\u7ebf\u96be\u4f8b\u6316\u6398&#xff08;Online Hard Example Mining&#xff0c;OHEM&#xff09;\u4ea4\u53c9\u71b5\u635f\u5931\u51fd\u6570&#xff0c;\u4e24\u4e2a\u7cfb\u6570\u90fd\u8bbe\u4e3a\u3002<\/p>\n<p>\u516c\u5f0f\u89e3\u8bfb&#xff1a; \u5206\u5272\u635f\u5931\u7ea6\u675f\u50cf\u7d20\u5206\u7c7b\u3001PMM\u635f\u5931\u7ea6\u675f\u7f3a\u5931\u8868\u793a\u9884\u6d4b\u3002\u5b8c\u6574\u7684\u8f93\u5165\u6837\u672c\u4e0d\u8ba1\u7b97\u7f3a\u5931\u76ee\u6807\u635f\u5931&#xff1b;\u63a8\u7406\u53bb\u6389\u6559\u5e08\u548c\u9884\u6d4b\u5668\u3002<\/p>\n<p>\u4e00\u53e5\u8bdd\u6982\u62ec\u8be5\u65b9\u6cd5\u5c31\u662f&#xff1a;\u4fdd\u6301\u5404\u4e2a\u4f20\u611f\u5668\u5404\u81ea\u72ec\u7acb\u5730\u8fdb\u884c\u9002\u914d&#xff0c;\u5728\u6b8b\u5dee\u8def\u5f84\u91cc\u4e92\u76f8\u4f20\u9012\u4fe1\u606f&#xff0c;\u5e76\u901a\u8fc7\u201c\u9884\u6d4b\u7a7a\u7f3a\u8005\u201d\u7684\u65b9\u5f0f\u6765\u57f9\u517b\u5197\u4f59\u7684\u80fd\u529b\u3002<\/p>\n<p>unsetunset6. \u5b9e\u9a8c\u7ed3\u679cunsetunset<\/p>\n<p>6.1 \u5b9e\u9a8c\u6761\u4ef6<\/p>\n<p>MCubeS \u5206\u4e3a \u4e8c\u5341\u7c7b\u6750\u6599&#xff0c;\u7528 RGB\u3001\u8fd1\u7ea2\u5916&#xff08;Near-Infrared&#xff0c;NIR&#xff09;\u3001\u7ebf\u504f\u632f\u89d2&#xff08;Angle of Linear Polarization&#xff0c;AoLP&#xff09;\u3001\u7ebf\u504f\u632f\u5ea6&#xff08;Degree of Linear Polarization&#xff0c;DoLP&#xff09;\u8fdb\u884c\u8bad\u7ec3\/\u9a8c\u8bc1\/\u6d4b\u8bd5&#xff0c;\u6570\u91cf\u4e3a&#xff1b;DELIVER \u5206\u4e3a \u4e8c\u5341\u4e94\u7c7b\u57ce\u5e02\u573a\u666f&#xff0c;\u4f7f\u7528 RGB\u3001\u6df1\u5ea6\u3001\u6fc0\u5149\u96f7\u8fbe&#xff08;Light Detection and Ranging&#xff0c;LiDAR&#xff09;\u3001\u4e8b\u4ef6\u7b49\u8fdb\u884c\u5212\u5206&#xff0c;\u6570\u91cf\u4e3a&#xff1b;MUSES \u5229\u7528\u5e27\u76f8\u673a\u3001\u4e8b\u4ef6\u548c LiDAR \u8fdb\u884c\u5212\u5206&#xff0c;\u4f46\u662f\u6ca1\u6709\u7ed9\u51fa\u5177\u4f53\u7684\u6570\u91cf\u3002\u6309\u7167MCubeS\/DELIVER\/MUSES\u7684\u987a\u5e8f\u6765\u7528\u4f5c\u4e3a\u8f93\u5165&#xff0c;\u6bcf\u7ec4\u5206\u522b\u505a\u8f6e&#xff0c;\u7528\u5f20 A5000\u548cAdamW\u521d\u59cb\u5b66\u4e60\u7387\u5206\u522b\u4e3a\u8fdb\u884c\u8bad\u7ec3&#xff0c;\u6700\u540e\u5f97\u5230\u7684\u8bc4\u4ef7\u6807\u51c6\u662f\u5e73\u5747\u4ea4\u5e76\u6bd4&#xff08;mean Intersection over Union&#xff0c;mIoU&#xff09;&#xff0c;\u5e76\u4e0eMAGIC\u3001Any2Seg\u3001StitchFusion\u7b49\u65b9\u6cd5\u8fdb\u884c\u6bd4\u8f83\u3002<\/p>\n<p>6.2 \u5b9a\u91cf\u7684\u7ed3\u679c<\/p>\n<p>MCSS \u4e0d\u540c\u914d\u7f6e\u7684\u5e73\u5747 mIoU&#xff1a;MCubeS \u4e3a&#xff0c;\u6bd4 StitchFusion \u7684\u63d0\u5347\u4e86\u4e2a\u767e\u5206\u70b9&#xff1b;MUSES \u4e3a&#xff1b;DELIVER \u4e3a&#xff0c;\u4f46\u662f\u5e76\u4e0d\u662f\u6240\u6709\u7684\u7ec4\u5408\u90fd\u662f\u6700\u597d\u7684&#xff0c;\u6bd4\u5982 RGB&#043;\u6df1\u5ea6&#043;LiDAR \u5c0f\u4e8e MAGIC\u3002<\/p>\n<p><img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/11\/20261101202511-6ae7a02792c08.png\" alt=\"\u56fe\u7247\" \/><\/p>\n<p>\u88681.&#xff1a; MCubeS\u7684MCSS\u7ed3\u679c&#xff0c;\u5bf9\u6bd4\u4e0d\u540c\u7684\u6a21\u5f0f\u7ec4\u5408\u548c\u53ef\u8bad\u7ec3\u53c2\u6570\u7684\u6570\u91cf\u3002<\/p>\n<p><img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/11\/20261101202511-6ae7a027b57fb.png\" alt=\"\u56fe\u7247\" \/><\/p>\n<p>\u88682.&#xff1a; MUSES\u7684MCSS\u7ed3\u679c\u3002<\/p>\n<p><img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/11\/20261101202511-6ae7a027d0b5f.png\" alt=\"\u56fe\u7247\" \/><\/p>\n<p>\u88683.&#xff1a; DELIVER\u7684MCSS\u7ed3\u679c\u3002<\/p>\n<p>MISS \u5bf9\u6240\u6709\u7684\u975e\u7a7a\u5b50\u96c6\u6c42\u5e73\u5747\u503c&#xff0c;\u5e76\u4e14\u5305\u542b\u4e86\u5b8c\u6574\u7684\u8f93\u5165\u7ec4\u5408&#xff0c;MCubeS \u7684\u503c\u662f&#xff0c;\u6bd4\u8868\u683c\u91cc\u6700\u9ad8\u7684\u73b0\u6709\u5747\u503c\u9ad8\u51fa&#xff1b;MUSES \u7684\u503c\u4e3a&#xff0c;\u6bd4 BiXFormer \u7684\u9ad8\u51fa&#xff1b;DELIVER \u7684\u503c\u4e3a&#xff0c;\u6bd4 Zheng \u7b49\u4eba\u7684\u9ad8\u51fa\u4e2a\u767e\u5206\u70b9\u3002<\/p>\n<p><img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/11\/20261101202512-6ae7a02822d48.png\" alt=\"\u56fe\u7247\" \/><\/p>\n<p>\u88684.&#xff1a; MUSES\u7684MISS\u7ed3\u679c&#xff0c;\u6240\u6709\u7684\u65b9\u6cd5\u90fd\u7528\u4e09\u79cd\u6a21\u5f0f\u8fdb\u884c\u8bad\u7ec3\u3002<\/p>\n<p><img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/11\/20261101202512-6ae7a02849cc5.png\" alt=\"\u56fe\u7247\" \/><\/p>\n<p>\u88685.&#xff1a; MCubeS\u7684MISS\u7ed3\u679c&#xff0c;\u6240\u6709\u7684\u65b9\u6cd5\u90fd\u7528\u56db\u79cd\u6a21\u6001\u8fdb\u884c\u8bad\u7ec3\u5e76\u4e14\u6bd4\u8f83\u4e86\u9884\u6d4b\u5668\u7684\u4e0d\u540c\u7248\u672c\u3002<\/p>\n<p><img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/11\/20261101202512-6ae7a02877eaf.png\" alt=\"\u56fe\u7247\" \/><\/p>\n<p>\u88686.&#xff1a; DELIVER\u7684MISS\u7ed3\u679c&#xff0c;\u6240\u6709\u7684\u65b9\u6cd5\u90fd\u7528\u56db\u79cd\u6a21\u6001\u8fdb\u884c\u8bad\u7ec3\u3002<\/p>\n<p>6.3 \u5b9a\u6027\u7684\u7ed3\u679c\u548c\u9c81\u68d2\u6027<\/p>\n<p>\u53ea\u6709RGB\u6216\u8005RGB&#043;LiDAR\u7684\u60c5\u51b5\u4e0b&#xff0c;FuseAdapt \u5206\u5272\u533a\u57df\u66f4\u52a0\u8fde\u7eed&#xff0c;\u6bd4CMNeXt\u3001StitchFusion\u5c11\u5927\u8303\u56f4\u9519\u8bef\u5206\u5272\u3002\u9884\u8bbe\u5929\u6c14\u4ee5\u53ca\u9000\u5316\u6761\u4ef6\u4e0b\u7684\u5e73\u5747mIoU\u503c\u4e3a&#xff0c;\u4f46\u662f\u591c\u665a\u548c\u6b20\u66dd\u5149\u4e0b\u8868\u73b0\u4e0d\u5982Any2Seg\u3002<\/p>\n<p><img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/11\/20261101202512-6ae7a028a4299.png\" alt=\"\u56fe\u7247\" \/><\/p>\n<p>\u56fe4.&#xff1a; DELIVER\u7684MISS\u5b9a\u6027\u6bd4\u8f83&#xff1a;\u56db\u6a21\u6001\u8bad\u7ec3&#xff0c;\u7b2c\u4e00\u884c\u53ea\u6709RGB&#xff0c;\u7b2c\u4e8c\u884c\u662fRGB&#043;LiDAR\u6d4b\u8bd5\u3002<\/p>\n<p>6.4 \u6d88\u878d\u5b9e\u9a8c<\/p>\n<p>\u5728 MCubeS \u5b8c\u5168\u56db\u6a21\u6001\u7684\u60c5\u51b5\u4e0b&#xff0c;\u72ec\u7acb\u9002\u914d\u540e\u7684\u7ecf\u8def\u7531\u4e3a&#xff0c;MISS \u53bb\u6389\u9884\u6d4b\u5668\u4e4b\u540e\u7684\u5747\u503c\u7531\u964d\u81f3&#xff0c;\u7ebf\u6027\u9884\u6d4b\u4e3a&#xff0c;\u5728 MiT-B0 \u9aa8\u5e72\u548c\u76f8\u540c\u7684\u8bad\u7ec3\u8bbe\u7f6e\u4e0b&#xff0c;FuseAdapt \u5728 MUSES \u53ef\u4ee5\u8fbe\u5230&#xff0c;\u6bd4 Adapter \u7684\u9ad8\u51fa\u5f88\u591a\u3002\u79e9\u4e3a\u3001\u6bcf\u4e00\u5c42\u52a0\u5165\u9002\u914d\u6a21\u5757\u7684\u65f6\u5019&#xff0c;MCubeS \u6240\u5f97\u5230\u7684\u7ed3\u679c\u6700\u597d\u3002<\/p>\n<p><img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/11\/20261101202513-6ae7a02900559.png\" alt=\"\u56fe\u7247\" \/><\/p>\n<p>\u88687.&#xff1a; \u4e0d\u540c\u4fe1\u606f\u6d41\u8bbe\u8ba1\u4e0b\u7684\u5b8c\u6574\u6a21\u6001mIoU\u3002<\/p>\n<p><img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/11\/20261101202513-6ae7a0291707d.png\" alt=\"\u56fe\u7247\" \/><\/p>\n<p>6.5 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