{"id":35825,"date":"2025-05-06T17:17:24","date_gmt":"2025-05-06T09:17:24","guid":{"rendered":"https:\/\/www.wsisp.com\/helps\/35825.html"},"modified":"2025-05-06T17:17:24","modified_gmt":"2025-05-06T09:17:24","slug":"ai%e7%94%9f%e6%88%90%e8%a7%86%e9%a2%91%e6%a3%80%e6%b5%8b%e6%96%b9%e6%b3%95%e5%8f%8a%e5%85%b6%e7%9b%b8%e5%85%b3%e7%a0%94%e7%a9%b6","status":"publish","type":"post","link":"https:\/\/www.wsisp.com\/helps\/35825.html","title":{"rendered":"AI\u751f\u6210\u89c6\u9891\u68c0\u6d4b\u65b9\u6cd5\u53ca\u5176\u76f8\u5173\u7814\u7a76"},"content":{"rendered":"<\/p>\n<h4>\u76ee\u5f55\u6807\u9898<\/h4>\n<ul>\n<li>\u30101\u3011AI-Generated Video Detection via Spatio-Temporal Anomaly Learning<\/li>\n<li>\u30102\u3011DeCoF: Generated Video Detection via Frame Consistency<\/li>\n<li>\n<ul>\n<li>\u30102.1\u3011Spatiotemporal Convolutional Neural Networks (STCNN) rely on spatial artifacts<\/li>\n<li>\u30102.2\u3011Capturing Universal Spatial Artifacts is Difficult<\/li>\n<\/ul>\n<\/li>\n<li>\u30103\u3011DeMamba: AI-Generated Video Detection on Million-Scale Benchmark<\/li>\n<li>\u30104\u3011GenVidBench: A Challenging Benchmark for Detecting AI-Generated Video<\/li>\n<li>\u30105\u3011Distinguish Any Fake Videos: Unleashing the Power of Large-scale Data and Motion Features<\/li>\n<li>\u30106\u3011On Learning Multi-Modal Forgery Representation for Diffusion Generated Video Detection<\/li>\n<li>\u30107\u3011What Matters in Detecting AI-Generated Videos like Sora?<\/li>\n<li>\u30108\u3011Turns Out I\u2019m Not Real: Towards Robust Detection of AI-Generated Videos<\/li>\n<li>\u30109\u3011Beyond Deepfake Images: Detecting AI-Generated Videos<\/li>\n<li>\u301010\u3011Exposing AI-generated Videos: A Benchmark Dataset and a Local-and-Global Temporal Defect Based Detection Method<\/li>\n<li>Acknowledgments<\/li>\n<\/ul>\n<h2>\u30101\u3011AI-Generated Video Detection via Spatio-Temporal Anomaly Learning<\/h2>\n<ul>\n<li>\u9488\u5bf9AI\u751f\u6210\u89c6\u9891\u5e26\u6765\u7684\u4f2a\u9020\u98ce\u9669&#xff0c;\u63d0\u51fa\u4e86\u4e00\u79cd\u57fa\u4e8e\u53cc\u5206\u652f\u65f6\u7a7a\u5377\u79ef\u795e\u7ecf\u7f51\u7edc\u7684\u68c0\u6d4b\u65b9\u6cd5AIGVDet&#xff0c;\u901a\u8fc7\u5206\u522b\u5efa\u6a21RGB\u5e27\u4e2d\u7684\u7a7a\u95f4\u7279\u5f81\u4e0e<font color=\"#0000FF\">\u5149\u6d41\u56fe\u4e2d\u7684\u65f6\u95f4\u7279\u5f81<\/font>&#xff0c;\u6709\u6548\u6355\u6349\u751f\u6210\u89c6\u9891\u4e2d\u7684\u5f02\u5e38\u75d5\u8ff9&#xff0c;\u5e76\u878d\u5408\u4e24\u8005\u7ed3\u679c\u4ee5\u63d0\u5347\u5224\u522b\u80fd\u529b\u3002\u4e3a\u652f\u6301\u6a21\u578b\u8bad\u7ec3\u4e0e\u8bc4\u4f30&#xff0c;\u6784\u5efa\u4e86<font color=\"#0000FF\">\u5927\u89c4\u6a21\u751f\u6210\u89c6\u9891\u6570\u636e\u96c6GVD<\/font>\u3002\u5b9e\u9a8c\u7ed3\u679c\u8868\u660e&#xff0c;\u8be5\u65b9\u6cd5\u5728\u9762\u5bf9\u672a\u77e5\u751f\u6210\u6a21\u578b\u4e0e\u89c6\u9891\u538b\u7f29\u7b49\u5e72\u6270\u65f6\u4ecd\u5177\u5907\u826f\u597d\u7684\u6cdb\u5316\u6027\u4e0e\u9c81\u68d2\u6027&#xff0c;\u5177\u5907\u6210\u4e3a\u751f\u6210\u89c6\u9891\u68c0\u6d4b\u4efb\u52a1\u7a33\u5065\u57fa\u7ebf\u7684\u6f5c\u529b\u3002\u4ee3\u7801\u548c\u6570\u636e\u96c6\u5df2\u5f00\u6e90\u4e8e&#xff1a;https:\/\/github.com\/multimediaFor\/AIGVDet\u3002<\/li>\n<\/ul>\n<p> <img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2025\/05\/20250506091710-6819d39629e7b.png\" width=\"100%\" \/> <\/p>\n<p> <b>AI\u751f\u6210\u89c6\u9891\u548c\u771f\u5b9e\u89c6\u9891\u7684\u5149\u6d41\u56fe<\/b> <\/p>\n<ul>\n<li>\u4f4e\u8d28\u91cf\u7684\u751f\u6210\u89c6\u9891\u53ef\u80fd\u4f1a\u5728\u5e27\u4e2d\u8868\u73b0\u51fa\u4e00\u4e9b\u5f02\u5e38\u73b0\u8c61&#xff0c;\u4f8b\u5982\u7eb9\u7406\u5f02\u5e38\u548c\u7269\u7406\u89c4\u5f8b\u7684\u8fdd\u80cc\u3002\u800c\u90a3\u4e9b\u8089\u773c\u96be\u4ee5\u5206\u8fa8\u7684\u9ad8\u8d28\u91cf\u751f\u6210\u89c6\u9891&#xff0c;\u5219\u66f4\u53ef\u80fd\u5728<font color=\"#0000FF\">\u5149\u6d41\u56fe\u4e2d\u8868\u73b0\u51fa\u65f6\u95f4\u4e0a\u7684\u4e0d\u8fde\u7eed\u6027<\/font>\u3002\u4e0a\u56fe\u5c55\u793a\u4e86\u4e00\u4e9b\u89c6\u9891\u5e27\u53ca\u5176\u901a\u8fc7RAFT\u65b9\u6cd5\u4f30\u8ba1\u5f97\u5230\u7684\u5149\u6d41\u56fe&#xff0c;\u5176\u4e2d\u989c\u8272\u8868\u793a\u8fd0\u52a8\u65b9\u5411&#xff0c;\u660e\u6697\u8868\u793a\u8fd0\u52a8\u5e45\u5ea6\u3002<font color=\"#0000FF\">\u5c3d\u7ba1\u751f\u6210\u89c6\u9891\u5e27\u5728\u89c6\u89c9\u4e0a\u5341\u5206\u903c\u771f&#xff0c;\u4f46\u5176\u5149\u6d41\u56fe\u76f8\u6bd4\u771f\u5b9e\u89c6\u9891\u66f4\u4e0d\u5e73\u6ed1&#xff0c;\u8f6e\u5ed3\u4e5f\u66f4\u52a0\u6a21\u7cca<\/font>\u3002<\/li>\n<\/ul>\n<p> <img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2025\/05\/20250506091710-6819d396be130.png\" width=\"100%\" \/> <\/p>\n<p> <b>AIGVDet<\/b> <\/p>\n<ul>\n<li>\u4e3a\u4e86\u6355\u6349\u771f\u5b9e\u89c6\u9891\u4e0e\u751f\u6210\u89c6\u9891\u4e4b\u95f4\u7684\u8fd9\u4e9b\u5dee\u5f02&#xff0c;\u6211\u4eec\u63d0\u51fa\u4e86\u4e00\u79cd\u7b80\u5355\u800c\u6709\u6548\u7684AI\u751f\u6210\u89c6\u9891\u68c0\u6d4b\u6a21\u578b&#xff08;AIGVDet&#xff09;\u3002\u8be5\u6a21\u578b\u4ee5RGB\u5e27\u53ca\u5176\u5bf9\u5e94\u7684\u5149\u6d41\u56fe\u4e3a\u8f93\u5165&#xff0c;\u5229\u7528\u53cc\u5206\u652f\u7684ResNet50\u7f16\u7801\u5668\u6df1\u5165\u6316\u6398\u8fd9\u4e24\u79cd\u6a21\u6001\u4e2d\u7684\u5f02\u5e38\u7279\u5f81\u3002\u6700\u7ec8&#xff0c;\u6211\u4eec\u6784\u5efa\u4e86\u4e00\u4e2a\u57fa\u4e8e\u51b3\u7b56\u7ea7\u878d\u5408\u7684\u4e8c\u5206\u7c7b\u5668&#xff0c;\u6709\u6548\u6574\u5408\u591a\u6e90\u4fe1\u606f\u4ee5\u63d0\u5347\u6a21\u578b\u7684\u5224\u522b\u80fd\u529b\u3002<\/li>\n<li>GVD\u6570\u636e\u96c6&#xff0c;\u6db5\u76d6\u4e86\u5f53\u524d\u6700\u5e38\u89c1\u7684\u4e24\u7c7b\u751f\u6210\u6a21\u578b&#xff1a;<font color=\"#FF00FF\">\u6587\u672c\u751f\u6210\u89c6\u9891&#xff08;Text-to-Video&#xff0c;T2V&#xff09;<\/font>\u548c<font color=\"#FF00FF\">\u56fe\u50cf\u751f\u6210\u89c6\u9891&#xff08;Image-to-Video&#xff0c;I2V&#xff09;<\/font>\u3002T2V\u6307\u7684\u662f\u6839\u636e\u6587\u672c\u5185\u5bb9\u81ea\u52a8\u751f\u6210\u76f8\u5e94\u7684\u89c6\u9891&#xff0c;\u800cI2V\u5219\u6307\u6839\u636e\u5e26\u6709\u63cf\u8ff0\u4fe1\u606f\u7684\u56fe\u50cf&#xff0c;\u6216\u4ec5\u6839\u636e\u56fe\u50cf\u751f\u6210\u89c6\u9891\u3002<\/li>\n<\/ul>\n<p> <img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2025\/05\/20250506091711-6819d397943b0.png\" width=\"100%\" \/> <\/p>\n<p> <b>Robustness evaluation<\/b> <\/p>\n<ul>\n<li>\u8bc4\u4f30\u4e86\u6a21\u578b\u5728\u9762\u5bf9<font color=\"#228B22\">\u89c6\u9891\u538b\u7f29<\/font>\u8fd9\u4e00\u73b0\u5b9e\u573a\u666f\u4e2d\u6700\u5e38\u89c1\u540e\u5904\u7406\u64cd\u4f5c\u65f6\u7684\u9c81\u68d2\u6027\u3002CRF\u662f\u63a7\u5236<font color=\"#228B22\">H.264\u538b\u7f29<\/font>\u8d28\u91cf\u7684\u53c2\u6570&#xff0c;\u6211\u4eec\u6d4b\u8bd5\u4e86CRF\u4e3a0\u300118\u300123\u548c28\u7684\u538b\u7f29\u7b49\u7ea7&#xff08;\u5176\u4e2d0\u8868\u793a\u65e0\u538b\u7f29&#xff09;\u3002\u5bf9\u4e8e\u751f\u6210\u89c6\u9891\u548c\u771f\u5b9e\u89c6\u9891&#xff0c;\u6211\u4eec\u5747\u8fdb\u884c\u4e86\u91cd\u65b0\u538b\u7f29\u5904\u7406\u3002\u968f\u7740\u538b\u7f29\u7a0b\u5ea6\u7684\u589e\u52a0&#xff0c;AUC\u548cACC\u6709\u6240\u4e0b\u964d\u3002\u7136\u800c&#xff0c;\u5bf9\u4e8e\u5404\u4e2a\u68c0\u6d4b\u6a21\u578b\u7684\u51c6\u786e\u7387&#xff08;ACC&#xff09;\u5747\u7ef4\u6301\u572880%\u4ee5\u4e0a&#xff0c;AUC\u4e5f\u59cb\u7ec8\u4fdd\u6301\u572888%\u4ee5\u4e0a\u3002<\/li>\n<\/ul>\n<h2>\u30102\u3011DeCoF: Generated Video Detection via Frame Consistency<\/h2>\n<ul>\n<li>\u6784\u5efa\u4e86\u4e00\u4e2a\u5305\u542b964\u6761\u63d0\u793a\u3001\u6db5\u76d6\u591a\u79cd\u751f\u6210\u6a21\u578b&#xff08;\u5305\u62ecSora\u4e0eVeo&#xff09;\u7684\u516c\u5f00\u6570\u636e\u96c6<font color=\"#0000FF\">GVF<\/font>&#xff0c;\u63d0\u51fa\u4e86\u4e00\u79cd\u57fa\u4e8e\u5e27\u4e00\u81f4\u6027\u7684\u68c0\u6d4b\u65b9\u6cd5DeCoF\u3002\u8be5\u65b9\u6cd5\u901a\u8fc7\u6d88\u9664\u7a7a\u95f4\u4f2a\u5f71\u5e72\u6270&#xff0c;\u4e13\u6ce8\u4e8e\u6355\u6349\u65f6\u95f4\u4f2a\u5f71&#xff0c;\u5177\u5907\u826f\u597d\u7684\u6cdb\u5316\u6027\u548c\u9c81\u68d2\u6027&#xff0c;\u5728\u591a\u4e2a\u672a\u77e5\u548c\u95ed\u6e90\u5546\u7528\u751f\u6210\u6a21\u578b\u4e0a\u5747\u8868\u73b0\u4f18\u5f02\u3002\u76f8\u5173\u4ee3\u7801\u548c\u6570\u636e\u96c6\u5c06\u5f00\u653e\u4e8e&#xff1a;https:\/\/github.com\/wuwuwuyue\/DeCoF\u3002<\/li>\n<li><font color=\"red\">\u4f2a\u5f71&#xff08;Artifact&#xff09;<\/font>\u662f\u6307\u5728\u56fe\u50cf\u6216\u89c6\u9891\u4e2d\u51fa\u73b0\u7684\u975e\u81ea\u7136\u3001\u4e0d\u771f\u5b9e\u7684\u75d5\u8ff9\u6216\u5931\u771f&#xff0c;\u901a\u5e38\u662f\u7531\u4e8e\u538b\u7f29\u3001\u5904\u7406\u6216\u751f\u6210\u7b97\u6cd5\u9020\u6210\u7684\u3002\u4f2a\u5f71\u672c\u8d28\u4e0a\u662f\u4e00\u79cd\u201c\u5f02\u5e38\u201d&#xff0c;\u4f1a\u80cc\u79bb\u81ea\u7136\u56fe\u50cf\u6216\u89c6\u9891\u7684\u89c4\u5f8b\u3002<\/li>\n<li><font color=\"#FF00FF\">\u7a7a\u95f4\u4f2a\u5f71&#xff08;Spatial Artifacts&#xff09;<\/font>&#xff1a;\u51fa\u73b0\u5728\u5355\u5e27\u56fe\u50cf\u4e2d&#xff0c;\u5982\u6a21\u7cca\u3001\u8fb9\u7f18\u4e0d\u8fde\u7eed\u3001\u7eb9\u7406\u5f02\u5e38\u3001\u5757\u72b6\u5931\u771f&#xff08;blockiness&#xff09;\u7b49\u3002<\/li>\n<li><font color=\"#228B22\">\u65f6\u95f4\u4f2a\u5f71&#xff08;Temporal Artifacts&#xff09;<\/font>&#xff1a;\u51fa\u73b0\u5728\u8fde\u7eed\u5e27\u4e4b\u95f4&#xff0c;\u8868\u73b0\u4e3a\u65f6\u95f4\u7ef4\u5ea6\u7684\u4e0d\u4e00\u81f4&#xff0c;\u5982&#xff1a; \u2022 \u8fd0\u52a8\u4e0d\u8fde\u7eed&#xff1a;\u7269\u4f53\u79fb\u52a8\u65f6\u7a81\u7136\u201c\u8df3\u52a8\u201d\u6216\u53d8\u5f62\u3002 \u2022 \u5149\u6d41\u4e0d\u7a33\u5b9a&#xff1a;\u8fde\u7eed\u5e27\u4e4b\u95f4\u7684\u5149\u6d41\u573a\u53d8\u5316\u5f02\u5e38\u3001\u4e0d\u5e73\u6ed1\u3002 \u2022 \u5e27\u95f4\u4e0d\u4e00\u81f4&#xff1a;\u524d\u540e\u5e27\u4e2d\u7269\u4f53\u7684\u7eb9\u7406\u3001\u4f4d\u7f6e\u6216\u72b6\u6001\u4e0d\u534f\u8c03\u3002<\/li>\n<\/ul>\n<p> <img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2025\/05\/20250506091711-6819d397d4fbc.png\" width=\"100%\" \/> <\/p>\n<p> <b>\u751f\u6210\u89c6\u9891\u4e2d\u7a7a\u95f4\u4f2a\u5f71\u4e0e\u65f6\u95f4\u4f2a\u5f71<\/b> <\/p>\n<ul>\n<li>\u7a7a\u95f4\u4f2a\u5f71\u5305\u62ec&#xff1a;(a) \u51e0\u4f55\u5916\u89c2\u9519\u8bef&#xff0c;(b) \u56fe\u50cf\u5e03\u5c40\u9519\u8bef&#xff0c;&#xff08;c&#xff09;\u9891\u7387\u4e0d\u4e00\u81f4&#xff0c;(d) \u989c\u8272\u4e0d\u5339\u914d&#xff1b;<\/li>\n<li>\u65f6\u95f4\u4f2a\u5f71\u4e3a&#xff1a;(e) \u5e27\u4e0e\u5e27\u4e4b\u95f4\u7684\u4e0d\u4e00\u81f4\u3002<\/li>\n<\/ul>\n<h3>\u30102.1\u3011Spatiotemporal Convolutional Neural Networks (STCNN) rely on spatial artifacts<\/h3>\n<ul>\n<li>\u4e3a\u4e86\u5206\u6790 STCNN \u7f51\u7edc\u5728\u8bad\u7ec3\u8fc7\u7a0b\u4e2d\u5230\u5e95\u5b66\u4e60\u4e86\u54ea\u4e9b\u4fe1\u606f&#xff0c;\u6216\u8005\u8bf4\u5b83\u5728\u533a\u5206\u771f\u5b9e\u4e0e\u4f2a\u9020\u89c6\u9891\u65f6\u4f9d\u8d56\u4e86\u54ea\u4e9b\u7279\u5f81&#xff0c;\u6211\u4eec\u8bbe\u8ba1\u4e86\u4e24\u4e2a\u65b0\u7684\u63a2\u6d4b\u5b9e\u9a8c&#xff0c;\u5e76\u5728\u76f8\u540c\u7684\u6a21\u578b\u6846\u67b6\u4e0b\u6784\u5efa\u4e86\u4e24\u4e2a\u65b0\u6570\u636e\u96c6\u8fdb\u884c\u6d4b\u8bd5\u3002<\/li>\n<li>\u7b2c\u4e00\u4e2a\u6570\u636e\u96c6\u5c06\u5f53\u524d\u6d4b\u8bd5\u96c6\u4e2d\u6240\u6709\u771f\u5b9e\u89c6\u9891\u7684\u5e27\u987a\u5e8f\u6253\u4e71&#xff0c;\u7834\u574f\u89c6\u9891\u7684\u65f6\u95f4\u8fde\u7eed\u6027&#xff0c;\u4ee5\u89c2\u5bdf\u6a21\u578b\u662f\u5426\u53ef\u4ee5\u4ec5\u901a\u8fc7\u65f6\u95f4\u4e0d\u8fde\u7eed\u6027\u6765\u8fdb\u884c\u533a\u5206\u3002<\/li>\n<li>\u7b2c\u4e8c\u4e2a\u6570\u636e\u96c6\u5219\u4ece\u5f53\u524d\u6d4b\u8bd5\u96c6\u4e2d\u7684\u4f2a\u9020\u89c6\u9891\u4e2d\u968f\u673a\u9009\u53d6\u4e00\u5e27&#xff0c;\u5e76\u5c06\u8be5\u5e27\u590d\u5236\u591a\u6b21&#xff0c;\u751f\u6210\u4e00\u4e2a\u53ea\u6709\u5355\u5e27\u5185\u5bb9\u7684\u89c6\u9891&#xff0c;\u7528\u4e8e\u89c2\u5bdf\u6a21\u578b\u662f\u5426\u53ef\u4ee5\u4ec5\u4f9d\u8d56\u7a7a\u95f4\u4f2a\u5f71\u8fdb\u884c\u533a\u5206\u3002<\/li>\n<\/ul>\n<p> <img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2025\/05\/20250506091712-6819d39877c31.png\" width=\"70%\" \/> <\/p>\n<ul>\n<li>\u4e0a\u8868\u4e2d\u7684\u5b9e\u9a8c\u7ed3\u679c\u8868\u660e&#xff0c;<font color=\"red\">STCNN\u8fc7\u4e8e\u4f9d\u8d56\u7a7a\u95f4\u4f2a\u5f71<\/font>&#xff0c;\u4ece\u800c\u5c06\u751f\u6210\u89c6\u9891\u68c0\u6d4b\u95ee\u9898\u9000\u5316\u4e3a\u4e00\u4e2a\u4e8c\u7ef4\u95ee\u9898\u3002\u7136\u800c&#xff0c;\u4ec5\u51ed STCNN \u5bf9\u7a7a\u95f4\u4f2a\u5f71\u7684\u4f9d\u8d56\u4ecd\u65e0\u6cd5\u89e3\u91ca\u5176\u5728\u9762\u5bf9\u672a\u89c1\u8fc7\u7684\u751f\u6210\u6a21\u578b\u65f6\u7f3a\u4e4f\u6cdb\u5316\u80fd\u529b\u7684\u539f\u56e0\u3002<\/li>\n<\/ul>\n<h3>\u30102.2\u3011Capturing Universal Spatial Artifacts is Difficult<\/h3>\n<ul>\n<li>\u5c06\u5f53\u524d\u7528\u4e8e\u751f\u6210\u56fe\u50cf\u68c0\u6d4b\u7684\u65b9\u6cd5\u8f6c\u5316\u4e3a\u56fe\u50cf\u7ea7\u68c0\u6d4b\u5668&#xff0c;\u5e76\u7528\u4e8e\u68c0\u6d4b\u751f\u6210\u89c6\u9891&#xff0c;\u5728 GVF \u6570\u636e\u96c6\u4e0a\u8fdb\u884c\u6d4b\u8bd5\u3002\u8fd9\u4e9b\u68c0\u6d4b\u5668\u5728\u8bc6\u522b\u7279\u5b9a\u751f\u6210\u6a21\u578b\u7684\u7a7a\u95f4\u4f2a\u5f71\u65b9\u9762\u8868\u73b0\u51fa\u8272&#xff0c;\u4f46\u540c\u6837<font color=\"#0000FF\">\u7f3a\u4e4f\u5bf9\u672a\u89c1\u751f\u6210\u6a21\u578b\u7684\u6cdb\u5316\u80fd\u529b<\/font>\u3002<\/li>\n<\/ul>\n<p> <img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2025\/05\/20250506091712-6819d398b4e95.png\" width=\"100%\" \/> <\/p>\n<p> <b>t-SNE\u53ef\u89c6\u5316\u56fe&#xff0c;\u56db\u79cd\u89c6\u9891\u751f\u6210\u6a21\u578b\u76f8\u5173\u7684\u771f\u5b9e\u89c6\u9891\u5e27\u4e0e\u4f2a\u9020\u89c6\u9891\u5e27\u7684\u5206\u5e03\u60c5\u51b5<\/b> <\/p>\n<p> <img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2025\/05\/20250506091713-6819d3991cae5.png\" width=\"100%\" \/> <\/p>\n<p> <b>\u771f\u5b9e\u89c6\u9891\u5e27\u4e0e\u7531\u4e0d\u540c\u89c6\u9891\u751f\u6210\u6a21\u578b\u751f\u6210\u7684\u4f2a\u9020\u89c6\u9891\u5e27\u7684\u5e73\u5747\u9891\u8c31\u5bf9\u6bd4\u56fe<\/b> <\/p>\n<ul>\n<li>\u7814\u7a76\u53d1\u73b0&#xff0c;\u867d\u7136\u73b0\u6709\u68c0\u6d4b\u5668\u80fd\u591f\u6709\u6548\u8bc6\u522b\u7531\u5df2\u89c1\u751f\u6210\u6a21\u578b\u4ea7\u751f\u7684\u89c6\u9891&#xff0c;\u539f\u56e0\u5728\u4e8e\u5176\u6210\u529f\u6355\u6349\u5230\u4e86\u7279\u5b9a\u6a21\u578b\u7684\u7a7a\u95f4\u4f2a\u5f71&#xff0c;\u4f46\u8fd9\u4e9b<font color=\"red\">\u4f2a\u5f71\u5728\u4e0d\u540c\u751f\u6210\u6a21\u578b\u4e4b\u95f4\u7f3a\u4e4f\u4e00\u81f4\u6027<\/font>&#xff0c;\u5bfc\u81f4\u68c0\u6d4b\u5668\u96be\u4ee5\u6cdb\u5316\u81f3\u672a\u89c1\u6a21\u578b\u3002\u901a\u8fc7\u5bf9\u4e0d\u540c\u5b50\u6570\u636e\u96c6\u7684\u7279\u5f81\u5206\u5e03\u8fdb\u884c\u53ef\u89c6\u5316\u5206\u6790&#xff0c;\u4ee5\u53ca\u5bf9\u751f\u6210\u89c6\u9891\u5e27\u7684\u9891\u8c31\u8fdb\u884c\u5bf9\u6bd4&#xff0c;\u5b9e\u9a8c\u8fdb\u4e00\u6b65\u9a8c\u8bc1\u4e86\u4e0d\u540c\u6a21\u578b\u6240\u5f15\u5165\u7684\u7a7a\u95f4\u4f2a\u5f71\u5dee\u5f02\u663e\u8457&#xff0c;\u56e0\u800c\u6784\u5efa\u5177\u5907\u666e\u9002\u6027\u7684\u7a7a\u95f4\u7279\u5f81\u68c0\u6d4b\u5668\u6781\u5177\u6311\u6218\u3002<\/li>\n<\/ul>\n<p> <img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2025\/05\/20250506091713-6819d3996ee52.png\" width=\"100%\" \/> <\/p>\n<p> <b>DeCoF<\/b> <\/p>\n<ul>\n<li>\u6211\u4eec\u9996\u5148\u4f7f\u7528\u9884\u8bad\u7ec3\u7684 CLIP:VIT \u63d0\u53d6\u771f\u5b9e\u89c6\u9891\u548c\u751f\u6210\u89c6\u9891\u7684\u7279\u5f81&#xff0c;\u4ee5\u6d88\u9664\u7a7a\u95f4\u4f2a\u5f71\u5bf9\u65f6\u95f4\u4f2a\u5f71\u6355\u6349\u7684\u5f71\u54cd\u3002\u968f\u540e&#xff0c;\u5229\u7528\u4e00\u4e2a\u7531\u4e24\u4e2a Transformer \u5c42\u548c\u4e00\u4e2a MLP \u5934\u7ec4\u6210\u7684\u9a8c\u8bc1\u6a21\u5757&#xff0c;\u5b66\u4e60\u771f\u5b9e\u89c6\u9891\u4e0e\u4f2a\u9020\u89c6\u9891\u5728\u5e27\u4e00\u81f4\u6027\u4e0a\u7684\u5dee\u5f02\u3002<\/li>\n<li>\u5728\u5b9e\u9645\u68c0\u6d4b\u573a\u666f\u4e2d&#xff0c;\u68c0\u6d4b\u5668\u5bf9\u672a\u89c1\u8fc7\u7684\u6270\u52a8\u7684\u9c81\u68d2\u6027\u540c\u6837\u81f3\u5173\u91cd\u8981\u3002\u5728\u8fd9\u91cc&#xff0c;\u6211\u4eec\u4e3b\u8981\u5173\u6ce8\u4e24\u79cd\u6270\u52a8\u5bf9\u68c0\u6d4b\u5668\u7684\u5f71\u54cd&#xff1a;<font color=\"#0000FF\">\u9ad8\u65af\u6a21\u7cca\u548cJPEG\u538b\u7f29<\/font>\u3002\u9ad8\u65af\u6a21\u7cca\u5728\u4e09\u4e2a\u7ea7\u522b&#xff08;\u03c3 &#061; 1, 2, 3&#xff09;\u4e0b\u6dfb\u52a0&#xff0c;JPEG\u538b\u7f29\u5728\u4e94\u4e2a\u7ea7\u522b&#xff08;\u8d28\u91cf &#061; 90, 80, 70, 60, 50&#xff09;\u4e0b\u6dfb\u52a0\u3002<\/li>\n<\/ul>\n<h2>\u30103\u3011DeMamba: AI-Generated Video Detection on Million-Scale Benchmark<\/h2>\n<ul>\n<li>\u9488\u5bf9\u7f3a\u4e4f\u9ad8\u8d28\u91cf\u6570\u636e\u96c6\u7684\u95ee\u9898&#xff0c;\u4f5c\u8005\u63d0\u51fa\u4e86<font color=\"red\">\u9996\u4e2a\u767e\u4e07\u7ea7\u5927\u89c4\u6a21 AI \u751f\u6210\u89c6\u9891\u68c0\u6d4b\u6570\u636e\u96c6 GenVideo<\/font>&#xff0c;\u5e76\u8bbe\u8ba1\u4e86\u4e24\u4e2a\u8bc4\u4f30\u4efb\u52a1\u8861\u91cf\u68c0\u6d4b\u5668\u7684\u6cdb\u5316\u80fd\u529b\u4e0e\u9c81\u68d2\u6027\u3002 \u2022 \u8de8\u751f\u6210\u5668\u5206\u7c7b\u4efb\u52a1&#xff1a;\u8bc4\u4f30\u8bad\u7ec3\u540e\u7684\u68c0\u6d4b\u5668\u5728\u9762\u5bf9\u4e0d\u540c\u751f\u6210\u5668\u65f6\u7684\u6cdb\u5316\u80fd\u529b&#xff1b; \u2022 \u9000\u5316\u89c6\u9891\u5206\u7c7b\u4efb\u52a1&#xff1a;\u8bc4\u4f30\u68c0\u6d4b\u5668\u5728\u9762\u5bf9\u4f20\u64ad\u8fc7\u7a0b\u4e2d\u8d28\u91cf\u4e0b\u964d\u7684\u89c6\u9891\u65f6\u7684\u9c81\u68d2\u6027\u3002<\/li>\n<li>\u6b64\u5916&#xff0c;\u4f5c\u8005\u8fd8\u63d0\u51fa\u4e86\u4e00\u4e2a\u5373\u63d2\u5373\u7528\u7684\u589e\u5f3a\u6a21\u5757\u2014\u2014<font color=\"#FF00FF\">Detail Mamba&#xff08;DeMamba&#xff09;<\/font>&#xff0c;\u8be5\u6a21\u5757\u901a\u8fc7\u5206\u6790\u89c6\u9891\u5728\u65f6\u95f4\u548c\u7a7a\u95f4\u7ef4\u5ea6\u4e0a\u7684\u4e0d\u4e00\u81f4\u6027\u6765\u8bc6\u522b AI \u751f\u6210\u89c6\u9891&#xff0c;\u4ee3\u7801\u4e0e\u6570\u636e\u96c6\u5c06\u5f00\u653e\u4e8e&#xff1a;https:\/\/github.com\/chenhaoxing\/DeMamba\u3002<\/li>\n<\/ul>\n<p> <img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2025\/05\/20250506091714-6819d39a85642.png\" width=\"100%\" \/> <\/p>\n<p> <b>GenVideo\u6570\u636e\u96c6\u4e2d\u771f\u5b9e\u89c6\u9891\u548c\u751f\u6210\u89c6\u9891\u7684\u7edf\u8ba1\u6570\u636e<\/b> <\/p>\n<p>  <img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2025\/05\/20250506091716-6819d39c962a1.png\" width=\"100%\" \/> <\/p>\n<p>  <b>Detail Mamba<\/b> <\/p>\n<ul>\n<li>\u8be5\u65b9\u6cd5\u5305\u62ec\u7279\u5f81\u7f16\u7801\u5668\u3001DeMamba\u6a21\u5757\u548cMLP\u5206\u7c7b\u5934\u3002\u9996\u5148&#xff0c;\u4f7f\u7528\u6700\u5148\u8fdb\u7684\u89c6\u89c9\u7f16\u7801\u5668&#xff08;\u5982<font color=\"red\">CLIP\u548cXCLIP<\/font>&#xff09;\u5bf9\u89c6\u9891\u5e27\u8fdb\u884c\u7f16\u7801&#xff0c;\u751f\u6210\u7279\u5f81\u5e8f\u5217\u3002<\/li>\n<li>\u7136\u540e&#xff0c;\u901a\u8fc7DeMamba\u6a21\u5757\u5bf9\u8fd9\u4e9b\u7279\u5f81\u8fdb\u884c\u7a7a\u95f4\u6574\u5408\u548c\u65f6\u7a7a\u4e00\u81f4\u6027\u5efa\u6a21\u3002\u8be5\u6a21\u5757\u901a\u8fc7\u8fde\u7eed\u626b\u63cf\u7b56\u7565\u6709\u6548\u6355\u6349\u89c6\u9891\u5e27\u4e4b\u95f4\u7684\u590d\u6742\u65f6\u7a7a\u5173\u7cfb\u3002<\/li>\n<li>\u6700\u540e&#xff0c;\u805a\u5408\u5168\u5c40\u548c\u5c40\u90e8\u7279\u5f81&#xff0c;\u7ed3\u5408MLP\u8fdb\u884c\u89c6\u9891\u7684\u771f\u4f2a\u5206\u7c7b\u3002\u8be5\u6a21\u578b\u901a\u8fc7\u4e8c\u5143\u4ea4\u53c9\u71b5\u635f\u5931\u8fdb\u884c\u8bad\u7ec3&#xff0c;\u65e8\u5728\u63d0\u9ad8\u68c0\u6d4bAI\u751f\u6210\u89c6\u9891\u7684\u51c6\u786e\u6027\u548c\u9c81\u68d2\u6027\u3002<\/li>\n<li>\u7531\u4e8e\u751f\u6210\u65b9\u6cd5\u8fed\u4ee3\u8fc5\u901f&#xff0c;\u6211\u4eec\u63d0\u51fa\u4e86\u8de8\u6570\u636e\u96c6\u6cdb\u5316\u4efb\u52a1&#xff0c;\u7528\u4e8e\u6d4b\u8bd5\u68c0\u6d4b\u5668\u7684\u6cdb\u5316\u80fd\u529b\u3002\u5177\u4f53\u6765\u8bf4&#xff0c;\u8be5\u4efb\u52a1\u5305\u62ec\u4e24\u79cd\u7c7b\u578b&#xff1a;1&#xff09;\u591a\u5bf9\u591a\u6cdb\u5316\u4efb\u52a1&#xff1b;2&#xff09;\u4e00\u5bf9\u591a\u6cdb\u5316\u4efb\u52a1\u3002<\/li>\n<li><font color=\"#FF00FF\">\u591a\u5bf9\u591a\u6cdb\u5316\u4efb\u52a1<\/font>\u6307\u572810\u4e2a\u57fa\u51c6\u7c7b\u522b\u4e0a\u8fdb\u884c\u8bad\u7ec3&#xff0c;\u7136\u540e\u5728\u5404\u4e2a\u5b50\u96c6\u53caood\u4e0a\u7684\u5e73\u5747\u68c0\u6d4b\u6027\u80fd\u8fdb\u884c\u6d4b\u8bd5\u3002<\/li>\n<li><font color=\"#FF00FF\">\u4e00\u5bf9\u591a\u6cdb\u5316\u4efb\u52a1<\/font>\u53c2\u8003\u4e86AI\u751f\u6210\u56fe\u50cf\u68c0\u6d4b\u7684\u76f8\u5173\u8bbe\u5b9a&#xff0c;\u4e0e\u591a\u5bf9\u591a\u4e0d\u540c&#xff0c;\u5b83\u662f\u5728\u4e00\u4e2a\u57fa\u51c6\u7c7b\u522b\u4e0a\u8bad\u7ec3&#xff0c;\u5e76\u5728\u5404\u4e2a\u5b50\u96c6\u53caood\u4e0a\u6d4b\u8bd5\u6cdb\u5316\u6027\u80fd\u3002<\/li>\n<li><font color=\"#FF00FF\">ood&#xff08;Out-Of-Distribution&#xff09;<\/font>&#xff0c;\u5728\u8bad\u7ec3\u6570\u636e\u5206\u5e03\u4e4b\u5916\u7684\u89c6\u9891\u5b50\u96c6&#xff0c;\u5373\u6a21\u578b\u5728\u8bad\u7ec3\u65f6\u672a\u89c1\u8fc7\u7684\u89c6\u9891\u7c7b\u578b\u6216\u751f\u6210\u65b9\u5f0f&#xff0c;\u7528\u4e8e\u6d4b\u8bd5\u6a21\u578b\u7684\u6cdb\u5316\u80fd\u529b\u3002<\/li>\n<li>\u7814\u7a76\u4e86\u516b\u79cd\u4e0d\u540c\u7c7b\u578b\u6270\u52a8\u5bf9\u68c0\u6d4b\u5668\u7684\u5f71\u54cd&#xff0c;\u5305\u62ec&#xff1a;H.264\u538b\u7f29\u3001JPEG\u538b\u7f29\u3001\u7ffb\u8f6c&#xff08;FLIP&#xff09;\u3001\u88c1\u526a&#xff08;Crop&#xff09;\u3001\u6587\u5b57\u6c34\u5370\u3001\u56fe\u50cf\u6c34\u5370\u3001\u9ad8\u65af\u566a\u58f0\u548c\u989c\u8272\u53d8\u6362\u3002<\/li>\n<\/ul>\n<h2>\u30104\u3011GenVidBench: A Challenging Benchmark for Detecting AI-Generated Video<\/h2>\n<p><img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2025\/05\/20250506091717-6819d39d49f06.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/><\/p>\n<ul>\n<li><font color=\"#0000FF\">GenVidBench<\/font>\u662f\u4e00\u4e2a\u9762\u5411 AI \u751f\u6210\u89c6\u9891\u68c0\u6d4b\u4efb\u52a1\u7684\u5927\u89c4\u6a21\u3001\u9ad8\u8d28\u91cf\u6570\u636e\u96c6&#xff0c;\u5177\u5907\u8de8\u6765\u6e90\u3001\u8de8\u751f\u6210\u5668\u3001\u6db5\u76d6\u591a\u79cd\u5148\u8fdb\u89c6\u9891\u751f\u6210\u6a21\u578b\u4ee5\u53ca\u4e30\u5bcc\u8bed\u4e49\u5206\u7c7b\u7b49\u7279\u70b9&#xff0c;\u65e8\u5728\u63d0\u5347\u68c0\u6d4b\u6a21\u578b\u7684\u6cdb\u5316\u80fd\u529b\u548c\u9c81\u68d2\u6027&#xff0c;\u5e76\u4e3a\u7814\u7a76\u8005\u5f00\u53d1\u548c\u8bc4\u4f30\u751f\u6210\u89c6\u9891\u68c0\u6d4b\u65b9\u6cd5\u63d0\u4f9b\u6807\u51c6\u57fa\u51c6\u548c\u5b9e\u9a8c\u652f\u6301\u3002<\/li>\n<li>GenVidBench\u6570\u636e\u96c6\u4e0d\u4ec5\u5305\u542b\u771f\u5b9e\u4e0e\u4f2a\u9020\u89c6\u9891\u7684\u6807\u7b7e&#xff0c;\u8fd8\u63d0\u4f9b\u4e30\u5bcc\u7684\u8bed\u4e49\u5185\u5bb9\u6807\u7b7e&#xff0c;\u4f8b\u5982\u7269\u4f53\u7c7b\u6bd4\u3001\u573a\u666f\u4f4d\u7f6e\u548c\u52a8\u4f5c\u884c\u4e3a\u7b49<\/li>\n<\/ul>\n<p> <img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2025\/05\/20250506091718-6819d39e912bb.png\" width=\"100%\" \/> <\/p>\n<ul>\n<li>\n<p>\u4e0a\u8868\u662fGenVidBench \u6570\u636e\u96c6\u4e2d\u771f\u5b9e\u4e0e\u751f\u6210\u89c6\u9891\u7684\u7edf\u8ba1\u4fe1\u606f\u3002GenVidBench \u5305\u542b\u75318\u79cd\u5148\u8fdb\u751f\u6210\u5668\u751f\u6210\u76848\u4e2a\u4f2a\u9020\u89c6\u9891\u5b50\u96c6\u4ee5\u53ca2\u4e2a\u771f\u5b9e\u89c6\u9891\u5b50\u96c6\u3002\u89c6\u9891\u5bf9\u662f\u6839\u636e\u751f\u6210\u6765\u6e90&#xff08;\u5982\u6587\u672c\u63d0\u793a\u6216\u56fe\u50cf&#xff09;\u8fdb\u884c\u5212\u5206\u7684\u3002 <img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2025\/05\/20250506091719-6819d39f23759.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/><\/p>\n<\/li>\n<li>\n<p>GVD \u548c GenVideo \u662f\u4e4b\u524d\u7684\u4e24\u4e2a\u91cd\u8981\u6570\u636e\u96c6&#xff0c;\u4f46\u5b83\u4eec\u6709\u4e00\u4e9b\u5c40\u9650\u6027&#xff0c;\u6bd4\u5982\u7f3a\u4e4f\u539f\u59cb\u7684\u751f\u6210\u63d0\u793a\u3001\u56fe\u50cf\u3001\u89c6\u9891\u5bf9\u3001\u8bed\u4e49\u6807\u7b7e\u548c\u8de8\u6765\u6e90\u8bbe\u7f6e\u3002\u8fd9\u610f\u5473\u7740\u8fd9\u4e9b\u6570\u636e\u96c6\u5728\u8bad\u7ec3\u96c6\u548c\u6d4b\u8bd5\u96c6\u5185\u5bb9\u76f8\u4f3c\u65f6&#xff0c;\u65e0\u6cd5\u6709\u6548\u533a\u5206\u4e0d\u540c\u573a\u666f\u7684\u95ee\u9898\u3002<\/p>\n<\/li>\n<li>\n<p>GVF \u5c1d\u8bd5\u89e3\u51b3\u8fd9\u4e9b\u95ee\u9898&#xff0c;\u63d0\u4f9b\u4e86\u63d0\u793a\u3001\u56fe\u50cf\u3001\u89c6\u9891\u5bf9\u548c\u8bed\u4e49\u6807\u7b7e&#xff0c;\u4f46\u7531\u4e8e\u6570\u636e\u96c6\u89c4\u6a21\u8f83\u5c0f&#xff08;\u4ec52.8k\u4e2a\u89c6\u9891&#xff09;&#xff0c;\u5b83\u4ecd\u7136\u9762\u4e34\u89c4\u6a21\u4e0d\u8db3\u7684\u95ee\u9898\u3002\u540c\u65f6&#xff0c;\u5b83\u4e5f\u6ca1\u6709\u8de8\u6765\u6e90\u8bbe\u7f6e&#xff0c;\u8fd9\u4f7f\u5f97\u5b83\u5728\u591a\u6837\u6027\u548c\u6311\u6218\u6027\u65b9\u9762\u6709\u6240\u6b20\u7f3a\u3002<\/p>\n<\/li>\n<li>\n<p>GenVidBench \u662f\u4e00\u79cd\u6539\u8fdb\u7684\u6570\u636e\u96c6&#xff0c;\u89c4\u6a21\u8fbe\u5230100,000\u4e2a\u89c6\u9891&#xff0c;\u6db5\u76d6\u4e86\u8bed\u4e49\u6807\u7b7e\u548c\u7528\u4e8e\u751f\u6210\u89c6\u9891\u7684\u63d0\u793a\/\u56fe\u50cf&#xff0c;\u5e76\u8fdb\u884c\u4e86\u8de8\u6765\u6e90\u8bbe\u7f6e&#xff0c;\u4ece\u800c\u4f7f\u5176\u5728\u5047\u89c6\u9891\u68c0\u6d4b\u65b9\u9762\u66f4\u5177\u6311\u6218\u6027\u3002<\/p>\n<\/li>\n<li>\n<p><font color=\"red\">\u201c\u8de8\u6765\u6e90\u8bbe\u7f6e\u201d&#xff08;Cross-source setting&#xff09;<\/font>\u6307\u7684\u662f\u5728\u6570\u636e\u96c6\u7684\u8bad\u7ec3\u96c6\u548c\u6d4b\u8bd5\u96c6\u4e2d&#xff0c;\u4f7f\u7528\u6765\u81ea\u4e0d\u540c\u6765\u6e90&#xff08;\u4f8b\u5982&#xff0c;\u4e0d\u540c\u7684\u89c6\u9891\u751f\u6210\u6a21\u578b\u3001\u4e0d\u540c\u7684\u8f93\u5165\u6570\u636e\u6216\u4e0d\u540c\u7684\u751f\u6210\u73af\u5883&#xff09;\u7684\u6570\u636e\u3002\u8fd9\u79cd\u8bbe\u7f6e\u7684\u76ee\u7684\u662f\u589e\u52a0\u6570\u636e\u7684\u591a\u6837\u6027&#xff0c;\u5e76\u51cf\u5c11\u6a21\u578b\u5728\u8bad\u7ec3\u65f6\u53ef\u80fd\u5b66\u4e60\u5230\u7684\u504f\u5dee&#xff0c;\u4f7f\u5176\u80fd\u591f\u66f4\u597d\u5730\u9002\u5e94\u4e0d\u540c\u6765\u6e90\u7684\u89c6\u9891\u751f\u6210&#xff0c;\u4ece\u800c\u63d0\u9ad8\u68c0\u6d4b\u5668\u7684\u6cdb\u5316\u80fd\u529b\u3002\u7b80\u5355\u6765\u8bf4&#xff0c;\u8de8\u6765\u6e90\u8bbe\u7f6e\u589e\u52a0\u4e86\u6570\u636e\u96c6\u7684\u591a\u6837\u6027\u548c\u590d\u6742\u6027&#xff0c;\u662f\u4e00\u79cd\u4e3a\u4e86\u63d0\u5347AI\u751f\u6210\u89c6\u9891\u68c0\u6d4b\u5668\u6027\u80fd\u800c\u91c7\u7528\u7684\u7b56\u7565\u3002<\/p>\n<\/li>\n<li>\n<p><font color=\"red\">\u201c\u89c6\u9891\u5bf9\u201d&#xff08;Video pairs&#xff09;<\/font>\u6307\u7684\u662f\u4e00\u5bf9\u76f8\u5173\u7684\u4e24\u6bb5\u89c6\u9891&#xff0c;\u901a\u5e38\u7528\u4e8e\u6bd4\u8f83\u548c\u5206\u6790\u3002\u5728\u751f\u6210\u89c6\u9891\u68c0\u6d4b\u7684\u4e0a\u4e0b\u6587\u4e2d&#xff0c;\u89c6\u9891\u5bf9\u901a\u5e38\u7531\u4ee5\u4e0b\u4e24\u79cd\u7c7b\u578b\u7ec4\u6210&#xff1a;<\/p>\n<li>\n<p>\u771f\u5b9e\u89c6\u9891\u4e0e\u751f\u6210\u89c6\u9891\u5bf9&#xff1a;\u4e00\u4e2a\u89c6\u9891\u6765\u81ea\u771f\u5b9e\u4e16\u754c&#xff0c;\u800c\u53e6\u4e00\u4e2a\u89c6\u9891\u5219\u662f\u7531AI\u751f\u6210\u6a21\u578b\u751f\u6210\u7684\u3002\u8fd9\u5bf9\u89c6\u9891\u53ef\u4ee5\u7528\u6765\u8fdb\u884c\u771f\u5047\u89c6\u9891\u7684\u5bf9\u6bd4&#xff0c;\u5e2e\u52a9\u68c0\u6d4b\u5668\u8bc6\u522b\u548c\u533a\u5206AI\u751f\u6210\u7684\u89c6\u9891\u548c\u771f\u5b9e\u89c6\u9891\u3002<\/p>\n<\/li>\n<li>\n<p>\u76f8\u540c\u63d0\u793a\u7684\u751f\u6210\u89c6\u9891\u5bf9&#xff1a;\u5bf9\u4e8e\u751f\u6210\u89c6\u9891&#xff0c;\u53ef\u80fd\u4f1a\u4f7f\u7528\u76f8\u540c\u7684\u8f93\u5165\u63d0\u793a\u6216\u6761\u4ef6\u751f\u6210\u4e0d\u540c\u7684\u89c6\u9891\u3002\u8fd9\u79cd\u60c5\u51b5\u4e0b&#xff0c;\u89c6\u9891\u5bf9\u4e2d\u7684\u4e24\u4e2a\u89c6\u9891\u6765\u81ea\u76f8\u540c\u7684\u751f\u6210\u6a21\u578b&#xff0c;\u4f46\u5b83\u4eec\u662f\u57fa\u4e8e\u76f8\u540c\u7684\u8f93\u5165\u751f\u6210\u7684&#xff0c;\u53ef\u4ee5\u7528\u6765\u5206\u6790\u4e0d\u540c\u751f\u6210\u6a21\u578b\u6216\u4e0d\u540c\u751f\u6210\u53c2\u6570\u4e0b&#xff0c;AI\u751f\u6210\u7684\u89c6\u9891\u4e4b\u95f4\u7684\u5dee\u5f02\u3002<\/p>\n<\/li>\n<li>\n<p>\u5728\u68c0\u6d4b\u4efb\u52a1\u4e2d&#xff0c;\u89c6\u9891\u5bf9\u7684\u4f7f\u7528\u6709\u52a9\u4e8e\u8bad\u7ec3\u6a21\u578b\u8bc6\u522b\u4e24\u4e2a\u89c6\u9891\u4e4b\u95f4\u7684\u5f02\u540c&#xff0c;\u7279\u522b\u662f\u5728\u5bf9\u6bd4\u771f\u5047\u89c6\u9891\u65f6&#xff0c;\u53ef\u4ee5\u901a\u8fc7\u76f4\u63a5\u6bd4\u8f83\u5b83\u4eec\u7684\u5185\u5bb9\u3001\u7279\u5f81\u3001\u98ce\u683c\u7b49\u6765\u63d0\u9ad8\u68c0\u6d4b\u7684\u7cbe\u5ea6\u3002<\/p>\n<\/li>\n<\/li>\n<\/ul>\n<h2>\u30105\u3011Distinguish Any Fake Videos: Unleashing the Power of Large-scale Data and Motion Features<\/h2>\n<p><img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2025\/05\/20250506091719-6819d39f6b211.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/><\/p>\n<ul>\n<li>DuB3D \u67b6\u6784\u6982\u89c8&#xff1a;\u4e0a\u65b9\u5206\u652f\u8868\u793a\u5916\u89c2\u5efa\u6a21\u7ec4\u4ef6&#xff0c;\u4ece\u539f\u59cb\u89c6\u9891\u5185\u5bb9\u4e2d\u63d0\u53d6\u65f6\u7a7a\u7279\u5f81&#xff1b;\u4e0b\u65b9\u5206\u652f\u8868\u793a\u8fd0\u52a8\u5efa\u6a21\u7ec4\u4ef6&#xff0c;\u4ece\u5149\u6d41\u4e2d\u63d0\u53d6\u8fd0\u52a8\u7279\u5f81\u3002<\/li>\n<li>\u4e0a\u65b9\u5206\u652f\u5904\u7406\u8fde\u7eed\u7684 N \u5e27\u56fe\u50cf&#xff0c;\u4e0b\u65b9\u5206\u652f\u5219\u4f7f\u7528\u95f4\u9694\u4e3a K \u5e27\u7684\u89c6\u9891\u5e27\u5bf9\u6765\u8ba1\u7b97\u5149\u6d41\u4f5c\u4e3a\u8f93\u5165\u3002<\/li>\n<li>\u5728\u7f51\u7edc\u4e2d&#xff0c;\u201c3DSwin\u201d \u6307\u7684\u662f Video Swin Transformer \u7684\u9636\u6bb5\u6a21\u5757\u3002<\/li>\n<\/ul>\n<h2>\u30106\u3011On Learning Multi-Modal Forgery Representation for Diffusion Generated Video Detection<\/h2>\n<ul>\n<li>\u63d0\u51fa\u4e86\u4e00\u79cd\u521b\u65b0\u7b97\u6cd5&#xff0c;\u79f0\u4e3a\u591a\u6a21\u6001\u68c0\u6d4b&#xff08;MM-Det&#xff09;&#xff0c;\u7528\u4e8e\u68c0\u6d4b\u6269\u6563\u751f\u6210\u7684\u89c6\u9891\u3002MM-Det \u5229\u7528\u5927\u89c4\u6a21\u591a\u6a21\u6001\u6a21\u578b&#xff08;LMMs&#xff09;\u6df1\u5c42\u6b21\u7684\u611f\u77e5\u80fd\u529b\u548c\u7efc\u5408\u7406\u89e3\u80fd\u529b&#xff0c;\u901a\u8fc7\u5728\u5176\u591a\u6a21\u6001\u7a7a\u95f4\u4e2d\u751f\u6210<font color=\"#FF00FF\">\u591a\u6a21\u6001\u4f2a\u9020\u8868\u793a&#xff08;MMFR&#xff09;<\/font>&#xff0c;\u63d0\u5347\u5176\u5bf9\u672a\u77e5\u4f2a\u9020\u5185\u5bb9\u7684\u68c0\u6d4b\u80fd\u529b\u3002\u6b64\u5916&#xff0c;MM-Det \u8fd8\u5f15\u5165\u4e86\u4e00\u79cd<font color=\"#FF00FF\">\u5e27\u5185\u4e0e\u8de8\u5e27\u6ce8\u610f\u529b\u673a\u5236&#xff08;IAFA&#xff09;<\/font>&#xff0c;\u7528\u4e8e\u65f6\u7a7a\u57df\u4e2d\u7684\u7279\u5f81\u589e\u5f3a&#xff1b;\u5e76\u901a\u8fc7\u52a8\u6001\u878d\u5408\u7b56\u7565\u4f18\u5316\u4f2a\u9020\u7279\u5f81\u7684\u878d\u5408\u8868\u73b0\u3002\u6211\u4eec\u8fd8\u6784\u5efa\u4e86\u4e00\u4e2a\u6db5\u76d6\u591a\u79cd\u4f2a\u9020\u89c6\u9891\u7684\u7efc\u5408\u6027\u6269\u6563\u89c6\u9891\u6570\u636e\u96c6&#xff0c;\u79f0\u4e3aDiffusion Video Forensics&#xff08;DVF&#xff09;\u3002 <img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2025\/05\/20250506091720-6819d3a031516.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/><\/li>\n<li>\u591a\u6a21\u6001\u68c0\u6d4b\u7f51\u7edc&#xff08;MM-Det&#xff09;\u7684\u67b6\u6784\u3002\u7ed9\u5b9a\u4e00\u4e2a\u8f93\u5165\u89c6\u9891&#xff0c;\u5927\u89c4\u6a21\u591a\u6a21\u6001\u6a21\u578b&#xff08;LMM&#xff09;\u5206\u652f\u63a5\u6536\u89c6\u9891\u5e27\u548c\u63d0\u793a\u8bed&#xff0c;\u751f\u6210\u591a\u6a21\u6001\u4f2a\u9020\u8868\u793a&#xff08;MMFR&#xff09;\u3002\u4ece\u89c6\u89c9\u7f16\u7801\u5668\u548c\u5927\u8bed\u8a00\u6a21\u578b\u4e2d\u63d0\u53d6\u7684\u9690\u85cf\u72b6\u6001\u7ec4\u6210\u4e86 MMFR&#xff0c;\u7528\u4e8e\u6355\u6349\u4e0d\u540c\u6269\u6563\u751f\u6210\u89c6\u9891\u4e2d\u7684\u4f2a\u9020\u75d5\u8ff9\u3002<\/li>\n<li>\u5728\u65f6\u7a7a&#xff08;ST&#xff09;\u5206\u652f\u4e2d&#xff0c;\u89c6\u9891\u9996\u5148\u901a\u8fc7 VQ-VAE \u8fdb\u884c\u91cd\u6784&#xff0c;\u653e\u5927\u6269\u6563\u4f2a\u9020\u4e2d\u7684\u7ec6\u8282\u5dee\u5f02&#xff0c;\u968f\u540e\u8f93\u5165\u81f3 CNN \u7f16\u7801\u5668&#xff0c;\u5e76\u7ecf\u8fc7\u201c\u5e27\u5185\u4e0e\u5e27\u95f4\u6ce8\u610f\u529b\u673a\u5236\u201d&#xff08;IAFA&#xff09;\u6a21\u5757\u3002IAFA \u7528\u4e8e\u63d0\u53d6\u57fa\u4e8e\u7a7a\u95f4\u4f2a\u5f71\u548c\u65f6\u95f4\u4e0d\u4e00\u81f4\u6027\u7684\u7279\u5f81\u3002<\/li>\n<li>\u6700\u540e&#xff0c;\u91c7\u7528\u52a8\u6001\u878d\u5408\u7b56\u7565\u5c06\u4e24\u79cd\u7279\u5f81\u7ed3\u5408&#xff0c;\u7528\u4e8e\u6700\u7ec8\u7684\u4f2a\u9020\u68c0\u6d4b\u5224\u65ad\u3002<\/li>\n<li>\u4e3a\u4e86\u5206\u6790\u6211\u4eec\u65b9\u6cd5\u7684\u9c81\u68d2\u6027&#xff0c;\u6211\u4eec\u57fa\u4e8e\u5e38\u89c1\u7684\u540e\u5904\u7406\u64cd\u4f5c\u5bf9 MM-Det \u8fdb\u884c\u4e86\u989d\u5916\u7684\u8bc4\u4f30\u3002\u6211\u4eec\u9009\u62e9\u4e86\u9ad8\u65af\u6a21\u7cca&#xff08;\u03c3 &#061; 3&#xff09;\u3001JPEG \u538b\u7f29&#xff08;\u8d28\u91cf Q &#061; 90&#xff09;\u3001<font color=\"#FF00FF\">\u7f29\u653e&#xff08;\u6bd4\u4f8b\u4e3a 0.7&#xff09;<\/font>\u3001\u65cb\u8f6c&#xff08;\u89d2\u5ea6\u4e3a 90\u00b0&#xff09;\u4ee5\u53ca\u4e0a\u8ff0\u6240\u6709\u64cd\u4f5c\u7684\u7ec4\u5408&#xff0c;\u4f5c\u4e3a\u73b0\u5b9e\u573a\u666f\u4e2d\u672a\u89c1\u7684\u6270\u52a8\u3002\u6d4b\u8bd5\u6837\u672c\u4ece DVF \u6570\u636e\u96c6\u4e2d\u9009\u53d6&#xff0c;\u5171\u5305\u542b 500 \u4e2a\u771f\u5b9e\u89c6\u9891\u548c 500 \u4e2a\u4f2a\u9020\u89c6\u9891\u3002\u5982\u8868 S3 \u6240\u793a&#xff0c;MM-Det \u5728\u8fd9\u4e9b\u64cd\u4f5c\u4e0b\u7684\u6027\u80fd\u4e0b\u964d\u4ecb\u4e8e 0.9%&#xff08;JPEG \u538b\u7f29&#xff09;\u5230 5.8%&#xff08;\u9ad8\u65af\u6a21\u7cca&#xff09;\u4e4b\u95f4&#xff0c;\u6240\u6709\u7ed3\u679c\u5747\u9ad8\u4e8e 86%\u3002\u8fd9\u8868\u660e\u6211\u4eec\u7684\u65b9\u6cd5\u5728\u8fd9\u4e9b\u5e72\u6270\u4e0b\u4f9d\u7136\u5177\u6709\u826f\u597d\u7684\u6709\u6548\u6027\u3002<\/li>\n<\/ul>\n<h2>\u30107\u3011What Matters in Detecting AI-Generated Videos like Sora?<\/h2>\n<ul>\n<li>\u5728\u672c\u7814\u7a76\u4e2d&#xff0c;\u4ece\u4e09\u4e2a\u57fa\u672c\u7ef4\u5ea6\u51fa\u53d1\u2014\u2014\u5916\u89c2\u3001\u8fd0\u52a8\u548c\u51e0\u4f55&#xff0c;\u63a2\u8ba8\u4e86\u8fd9\u4e00\u5dee\u8ddd&#xff0c;\u5e76\u5c06\u771f\u5b9e\u89c6\u9891\u4e0e\u5f53\u524d\u6700\u5148\u8fdb\u7684 AI \u6a21\u578b Stable Video Diffusion \u6240\u751f\u6210\u7684\u89c6\u9891\u8fdb\u884c\u6bd4\u8f83\u3002\u4e3a\u6b64&#xff0c;\u6211\u4eec\u5229\u7528\u4e09\u7ef4\u5377\u79ef\u7f51\u7edc\u8bad\u7ec3\u4e86\u4e09\u4e2a\u5206\u7c7b\u5668&#xff0c;\u5206\u522b\u9488\u5bf9<font color=\"#FF00FF\">\u5916\u89c2&#xff08;\u4f7f\u7528\u89c6\u89c9\u57fa\u7840\u6a21\u578b\u7279\u5f81&#xff09;\u3001\u8fd0\u52a8&#xff08;\u4f7f\u7528\u5149\u6d41\u4fe1\u606f&#xff09;\u548c\u51e0\u4f55\u7ed3\u6784&#xff08;\u4f7f\u7528\u5355\u76ee\u6df1\u5ea6\u4fe1\u606f&#xff09;<\/font>\u8fdb\u884c\u4f2a\u9020\u68c0\u6d4b\u3002\u6bcf\u4e2a\u5206\u7c7b\u5668\u5728\u5b9a\u6027\u548c\u5b9a\u91cf\u4e0a\u5747\u8868\u73b0\u51fa\u51fa\u8272\u7684\u4f2a\u9020\u89c6\u9891\u8bc6\u522b\u80fd\u529b&#xff0c;\u8fd9\u8868\u660e\u5f53\u524d\u7684 AI \u751f\u6210\u89c6\u9891\u4ecd\u6613\u88ab\u8bc6\u522b&#xff0c;\u771f\u5b9e\u4e0e\u4f2a\u9020\u89c6\u9891\u4e4b\u95f4\u4f9d\u7136\u5b58\u5728\u663e\u8457\u5dee\u8ddd\u3002<\/li>\n<li>\u6b64\u5916&#xff0c;\u6211\u4eec\u901a\u8fc7 <font color=\"#FF00FF\">Grad-CAM&#xff08;\u80fd\u591f\u5728\u8f93\u5165\u56fe\u50cf\u4e0a\u9ad8\u4eae\u663e\u793a\u6a21\u578b\u5173\u6ce8\u7684\u533a\u57df&#xff0c;\u4e5f\u5c31\u662f\u8bf4&#xff0c;\u5b83\u544a\u8bc9\u6211\u4eec\u6a21\u578b\u662f\u201c\u770b\u7740\u201d\u56fe\u50cf\u7684\u54ea\u4e2a\u90e8\u5206\u6765\u5224\u65ad\u67d0\u4e00\u7c7b\u522b\u7684&#xff09;<\/font> \u6280\u672f\u8fdb\u4e00\u6b65\u5b9a\u4f4d\u4e86 AI \u751f\u6210\u89c6\u9891\u5728\u5916\u89c2\u3001\u8fd0\u52a8\u548c\u51e0\u4f55\u5c42\u9762\u4e0a\u7684\u7cfb\u7edf\u6027\u7f3a\u9677\u3002\u6700\u540e&#xff0c;\u6211\u4eec\u63d0\u51fa\u4e86\u4e00\u79cd\u4e13\u5bb6\u96c6\u6210\u6a21\u578b&#xff08;Ensemble-of-Experts&#xff09;&#xff0c;\u878d\u5408\u4e86\u5916\u89c2\u3001\u5149\u6d41\u548c\u6df1\u5ea6\u4fe1\u606f\u4ee5\u63d0\u5347\u4f2a\u9020\u89c6\u9891\u68c0\u6d4b\u7684\u9c81\u68d2\u6027\u4e0e\u6cdb\u5316\u80fd\u529b\u3002\u8be5\u6a21\u578b\u751a\u81f3\u80fd\u591f\u9ad8\u7cbe\u5ea6\u5730\u68c0\u6d4b\u7531 Sora \u751f\u6210\u7684\u89c6\u9891&#xff0c;\u5373\u4fbf\u5728\u8bad\u7ec3\u9636\u6bb5\u4ece\u672a\u89c1\u8fc7\u4efb\u4f55 Sora \u7684\u6837\u672c\u3002\u8fd9\u8868\u660e&#xff0c;\u771f\u5b9e\u4e0e\u4f2a\u9020\u89c6\u9891\u4e4b\u95f4\u7684\u5dee\u8ddd\u5177\u6709\u4e00\u5b9a\u7684\u666e\u9002\u6027&#xff0c;\u53ef\u63a8\u5e7f\u5230\u4e0d\u540c\u7684\u89c6\u9891\u751f\u6210\u6a21\u578b\u4e2d\u3002 <img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2025\/05\/20250506091721-6819d3a119eae.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/><\/li>\n<li>Ensembled Experts\u6a21\u578b\u7684\u6574\u4f53\u6846\u67b6\u6982\u89c8\u3002\u6bcf\u4e2aCVR\u5206\u7c7b\u5668\u90fd\u4f1a\u72ec\u7acb\u8bc4\u4f30\u8f93\u5165\u89c6\u9891\u7684\u771f\u5b9e\u6027\u3002\u5404\u4e2a\u5206\u7c7b\u5668\u751f\u6210\u7684logits\u88ab\u96c6\u6210&#xff0c;\u7528\u4e8e\u6784\u5efa\u6700\u7ec8\u7684\u4e13\u5bb6\u96c6\u6210\u6a21\u578b\u3002<\/li>\n<li><font color=\"#0000FF\">Logits\u662f\u6307\u795e\u7ecf\u7f51\u7edc\u8f93\u51fa\u5c42\u5728\u6fc0\u6d3b\u51fd\u6570&#xff08;\u5982 softmax&#xff09;\u4e4b\u524d\u7684\u539f\u59cb\u8f93\u51fa\u503c&#xff0c;\u901a\u5e38\u662f\u4e00\u4e2a\u5b9e\u6570\u5411\u91cf&#xff0c;\u8868\u793a\u6bcf\u4e2a\u7c7b\u522b\u7684\u201c\u672a\u5f52\u4e00\u5316\u7f6e\u4fe1\u5ea6\u201d<\/font>\u3002<\/li>\n<\/ul>\n<h2>\u30108\u3011Turns Out I\u2019m Not Real: Towards Robust Detection of AI-Generated Videos<\/h2>\n<p><img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2025\/05\/20250506091721-6819d3a1c3d22.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/><\/p>\n<ul>\n<li>\u4e0e\u4ee5\u5f80\u4ec5\u5229\u7528DIRE\u503c\u8bad\u7ec3CNN\u68c0\u6d4b\u5668\u7684\u5148\u8fdb\u65b9\u6cd5\u4e0d\u540c&#xff0c;DIVID\u540c\u65f6\u5229\u7528RGB\u5e27\u548c<font color=\"#FF00FF\">DIRE\u503c<\/font>&#xff0c;\u7ed3\u5408\u7b80\u5355\u7684CNN&#043;LSTM\u67b6\u6784&#xff0c;\u80fd\u591f\u6355\u6349\u89c6\u9891\u4e2d\u7684\u65f6\u95f4\u4fe1\u606f&#xff0c;\u5e76\u4ece\u591a\u4e2a\u89c6\u9891\u5e27\u4e2d\u63d0\u53d6\u663e\u5f0f\u77e5\u8bc6\u3002<\/li>\n<li><font color=\"#FF00FF\">\u6269\u6563\u91cd\u5efa\u8bef\u5dee&#xff08;DIRE&#xff09;<\/font>&#xff0c;\u8fd9\u662f\u4e00\u79cd\u901a\u8fc7\u6269\u6563\u6a21\u578b\u5bf9\u56fe\u50cf\u8fdb\u884c\u91cd\u5efa\u540e&#xff0c;\u4e0e\u539f\u56fe\u4e4b\u95f4\u7684\u5dee\u5f02\u6765\u8861\u91cf\u7684\u8bef\u5dee&#xff0c;\u7528\u4e8e\u8f85\u52a9\u68c0\u6d4b\u56fe\u50cf\u6216\u89c6\u9891\u7684\u771f\u5b9e\u6027\u3002 <img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2025\/05\/20250506091722-6819d3a21cc1a.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/><\/li>\n<li><font color=\"#0000FF\">\u4e0e\u6269\u6563\u751f\u6210\u56fe\u50cf\u76f8\u6bd4&#xff0c;\u771f\u5b9e\u56fe\u50cf\u7684DIRE\u503c\u901a\u5e38\u66f4\u5927<\/font>\u3002<\/li>\n<\/ul>\n<h2>\u30109\u3011Beyond Deepfake Images: Detecting AI-Generated Videos<\/h2>\n<ul>\n<li>\u672c\u6587\u5c55\u793a\u4e86\u5408\u6210\u56fe\u50cf\u68c0\u6d4b\u5668\u65e0\u6cd5\u53ef\u9760\u68c0\u6d4bAI\u751f\u6210\u7684\u89c6\u9891&#xff0c;\u5e76\u8bc1\u660e\u8fd9\u4e00\u95ee\u9898\u5e76\u975e\u7531H.264\u538b\u7f29\u5e26\u6765\u7684\u964d\u7ea7\u6548\u5e94\u6240\u81f4\u3002<\/li>\n<li>\u6211\u4eec\u53d1\u73b0\u5408\u6210\u89c6\u9891\u751f\u6210\u5668\u7559\u4e0b\u7684\u53d6\u8bc1\u75d5\u8ff9\u4e0e\u5408\u6210\u56fe\u50cf\u751f\u6210\u5668\u663e\u8457\u4e0d\u540c&#xff0c;\u5bfc\u81f4\u56fe\u50cf\u68c0\u6d4b\u5668\u5728\u89c6\u9891\u68c0\u6d4b\u4e2d\u8868\u73b0\u4e0d\u4f73\u3002<\/li>\n<li>\u540c\u65f6&#xff0c;\u6211\u4eec\u5c55\u793a\u4e86\u5408\u6210\u89c6\u9891\u7684\u53d6\u8bc1\u75d5\u8ff9\u53ef\u4ee5\u88ab\u5b66\u4e60&#xff0c;\u5e76\u5728H.264\u518d\u538b\u7f29\u7684\u60c5\u51b5\u4e0b\u5b9e\u73b0\u53ef\u9760\u7684\u89c6\u9891\u68c0\u6d4b\u548c\u751f\u6210\u6e90\u5f52\u5c5e\u3002\u5c3d\u7ba1\u901a\u8fc7\u96f6\u6837\u672c\u8fc1\u79fb\u68c0\u6d4b\u65b0\u751f\u6210\u5668\u7684\u89c6\u9891\u5177\u6709\u6311\u6218\u6027&#xff0c;\u4f46\u5c11\u91cf\u6837\u672c\u5b66\u4e60\u80fd\u51c6\u786e\u68c0\u6d4b\u65b0\u751f\u6210\u5668\u7684\u89c6\u9891\u3002\u6b64\u5916&#xff0c;\u672c\u6587\u521b\u5efa\u4e86\u4e00\u4e2a\u516c\u5f00\u7684\u5408\u6210\u89c6\u9891\u6570\u636e\u96c6&#xff0c;\u53ef\u7528\u4e8e\u8bad\u7ec3\u548c\u8bc4\u4f30\u5408\u6210\u89c6\u9891\u68c0\u6d4b\u5668\u7684\u6027\u80fd\u3002<\/li>\n<\/ul>\n<h2>\u301010\u3011Exposing AI-generated Videos: A Benchmark Dataset and a Local-and-Global Temporal Defect Based Detection Method<\/h2>\n<ul>\n<li>\u57fa\u4e8e\u5bf9\u751f\u6210\u89c6\u9891\u4e2d\u65f6\u95f4\u7f3a\u9677\u7684\u5206\u6790&#xff0c;\u6211\u4eec\u63d0\u51fa\u4e86\u4e00\u4e2a\u65b0\u9896\u7684\u68c0\u6d4b\u6846\u67b6&#xff0c;\u7efc\u5408\u8003\u8651\u5c40\u90e8\u8fd0\u52a8\u4fe1\u606f\u4e0e\u5168\u5c40\u5916\u89c2\u53d8\u5316\u3002\u540c\u65f6&#xff0c;\u8bbe\u8ba1\u4e86\u57fa\u4e8e\u901a\u9053\u6ce8\u610f\u529b\u7684\u7279\u5f81\u878d\u5408\u6a21\u5757&#xff0c;\u80fd\u591f\u81ea\u9002\u5e94\u5730\u7ed3\u5408\u5c40\u90e8\u4e0e\u5168\u5c40\u65f6\u95f4\u7ebf\u7d22&#xff0c;\u4ee5\u63ed\u793a\u4f2a\u9020\u89c6\u9891\u3002 <img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2025\/05\/20250506091722-6819d3a2adf6b.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" 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color=\"#FF00FF\">\u5c40\u90e8\u8fd0\u52a8\u4fe1\u606f<\/font>\u3002<\/li>\n<li>\u91c7\u7528 BEiT v2 \u4f5c\u4e3a\u9884\u8bad\u7ec3\u7684\u89c6\u89c9\u7279\u5f81\u63d0\u53d6\u5668&#xff0c;\u5b83\u57fa\u4e8e\u63a9\u7801\u56fe\u50cf\u5efa\u6a21\u6846\u67b6&#xff0c;\u5e76\u901a\u8fc7\u5411\u91cf\u91cf\u5316\u84b8\u998f\u964d\u4f4e\u4e86\u89c6\u89c9\u7279\u5f81\u5bf9\u56fe\u50cf\u7ec6\u8282\u53d8\u5316\u7684\u654f\u611f\u6027&#xff0c;\u540c\u65f6\u4fdd\u7559\u9ad8\u7ea7\u8bed\u4e49\u4fe1\u606f\u3002\u56e0\u6b64&#xff0c;\u5168\u5c40\u5916\u89c2\u53d8\u5316\u7684\u7279\u5f81\u5b66\u4e60\u8fc7\u7a0b\u53ef\u8868\u793a\u4e3a&#xff1a;\u8f93\u5165\u5e27\u7684\u89c6\u89c9\u7279\u5f81\u4f9d\u65f6\u95f4\u987a\u5e8f\u8f93\u5165\u81f3\u53ef\u8bad\u7ec3\u7684\u65f6\u95f4 Transformer \u6a21\u578b\u4e2d&#xff0c;\u4ece\u800c\u83b7\u53d6\u8868\u793a<font color=\"#FF00FF\">\u5168\u5c40\u5916\u89c2\u53d8\u5316<\/font>\u7684\u7279\u5f81\u8868\u793a\u3002<\/li>\n<li>\u57fa\u4e8e<font color=\"#FF00FF\">\u901a\u9053\u6ce8\u610f\u529b&#xff08;Channel Attention, CA&#xff09;\u7684\u7279\u5f81\u878d\u5408\u6a21\u5757<\/font>&#xff0c;\u7528\u4e8e\u878d\u5408\u5c40\u90e8\u8fd0\u52a8\u7279\u5f81\u4e0e\u5168\u5c40\u5916\u89c2\u7279\u5f81\u3002<\/li>\n<li>\u9c81\u68d2\u6027\u8bc4\u4f30&#xff1a;\u5728\u89c6\u9891\u4e2d\u8fdb\u884c <font color=\"#228B22\">\u6bd4\u7279\u9519\u8bef&#xff08;Bit Error&#xff09;<\/font> \u64cd\u4f5c&#xff0c;\u901a\u5e38\u662f\u6307\u5728\u89c6\u9891\u7684\u4e8c\u8fdb\u5236\u6570\u636e\u4e2d\u4eba\u4e3a\u5730\u5f15\u5165\u968f\u673a\u7684\u6bd4\u7279\u7ffb\u8f6c&#xff0c;\u4ee5\u6a21\u62df\u4f20\u8f93\u8fc7\u7a0b\u4e2d\u7531\u4e8e\u4fe1\u9053\u566a\u58f0\u6216\u786c\u4ef6\u9519\u8bef\u9020\u6210\u7684\u6570\u636e\u7834\u574f\u3002\u8fd9\u662f\u6a21\u62df\u7f51\u7edc\u4f20\u8f93\u9519\u8bef\u6216\u5b58\u50a8\u4ecb\u8d28\u635f\u574f\u7684\u4e00\u79cd\u5e38\u89c1\u65b9\u5f0f\u3002<\/li>\n<\/ul>\n<h2>Acknowledgments<\/h2>\n<ul>\n<li>I would like to express my sincere gratitude to the authors of the cited works for their valuable contributions to this field. Their research laid the foundation for this review, and their insights greatly enriched the discussion.<\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>\u6587\u7ae0\u6d4f\u89c8\u9605\u8bfb873\u6b21\uff0c\u70b9\u8d5e17\u6b21\uff0c\u6536\u85cf26\u6b21\u3002AI-Generated Video Detection<\/p>\n","protected":false},"author":2,"featured_media":35806,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[175,50,86,3059,3058,523],"topic":[],"class_list":["post-35825","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-server","tag-chatgpt","tag-50","tag-86","tag-3059","tag-3058","tag-523"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v20.3 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>AI\u751f\u6210\u89c6\u9891\u68c0\u6d4b\u65b9\u6cd5\u53ca\u5176\u76f8\u5173\u7814\u7a76 - \u7f51\u7855\u4e92\u8054\u5e2e\u52a9\u4e2d\u5fc3<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.wsisp.com\/helps\/35825.html\" \/>\n<meta property=\"og:locale\" content=\"zh_CN\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"AI\u751f\u6210\u89c6\u9891\u68c0\u6d4b\u65b9\u6cd5\u53ca\u5176\u76f8\u5173\u7814\u7a76 - 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