{"id":38291,"date":"2025-02-13T14:00:53","date_gmt":"2025-02-13T06:00:53","guid":{"rendered":"https:\/\/17aitech.com\/?p=38291"},"modified":"2025-02-13T14:00:53","modified_gmt":"2025-02-13T06:00:53","slug":"%e8%b6%85-1-2-%e4%b8%87%e4%ba%ba%e5%8f%82%e5%8a%a0-cvpr-2024%ef%bc%8c%e8%b0%b7%e6%ad%8c%e7%a0%94%e7%a9%b6%e9%99%a2%e8%8e%b7%e5%be%97%e6%9c%80%e4%bd%b3%e8%ae%ba%e6%96%87","status":"publish","type":"post","link":"https:\/\/17aitech.com\/?p=38291","title":{"rendered":"\u8d85 1.2 \u4e07\u4eba\u53c2\u52a0 CVPR 2024\uff0c\u8c37\u6b4c\u7814\u7a76\u9662\u83b7\u5f97\u6700\u4f73\u8bba\u6587"},"content":{"rendered":"

\u4f5c\u8005\uff1a\u8d56\u6587\u6615 \u9a6c\u854a\u857e<\/p>\n

\u7f16\u8f91\uff1a\u9648\u5f69\u5a34<\/p>\n

\u5317\u4eac\u65f6\u95f4\u4eca\u5929\u51cc\u6668\uff0c\u7f8e\u56fd\u897f\u96c5\u56fe\u6b63\u5728\u53ec\u5f00\u7684\u8ba1\u7b97\u673a\u89c6\u89c9\u76db\u4f1a CVPR 2024 \u6b63\u5f0f\u516c\u5e03\u4e86\u6700\u4f73\u8bba\u6587\u7b49\u5956\u9879\u3002\u4eca\u5e74\u5171\u6709 2 \u7bc7\u8bba\u6587\u83b7\u5f97\u4e86\u8fd9\u4efd\u5168\u7403\u6700\u91cd\u8981\u7684\u8ba1\u7b97\u673a\u89c6\u89c9\u9886\u57df\u7684\u5927\u5956\uff0c\u56e2\u961f\u6210\u5458\u5206\u522b\u6765\u81ea\u8c37\u6b4c\u7814\u7a76\u9662\u3001\u52a0\u5dde\u5927\u5b66\u5723\u5730\u4e9a\u54e5\u5206\u6821\u3001\u5357\u52a0\u5dde\u5927\u5b66\u3001\u5251\u6865\u5927\u5b66\u53ca\u5e03\u5170\u8fea\u65af\u5927\u5b66\u3002<\/p>\n

\u672c\u5468\uff086.17-6.21\uff09\uff0c\u7b2c\u56db\u5341\u4e00\u5c4a\u56fd\u9645\u8ba1\u7b97\u673a\u89c6\u89c9\u4e0e\u6a21\u5f0f\u8bc6\u522b\u4f1a\u8bae\uff08CVPR\uff09\u5728\u7f8e\u56fd\u897f\u96c5\u56fe\u62c9\u5f00\u5e37\u5e55\u3002\u6839\u636eCVPR\u5b98\u65b9\u7684\u6700\u65b0\u516c\u544a\uff0cCVPR 2024\u5df2\u7ecf\u6210\u4e3a\u8be5\u4f1a\u8bae\u5386\u53f2\u4e0a\u89c4\u6a21\u6700\u5927\u3001\u53c2\u4e0e\u4eba\u6570\u6700\u591a\u7684\u4e00\u5c4a\uff0c\u622a\u6b626\u670819\u65e5\uff0c\u73b0\u573a\u53c2\u4f1a\u4eba\u6570\u5df2\u8d85\u8fc7\u4e00\u4e07\u4e24\u5343\u4eba\u3002<\/p>\n

\u4f5c\u4e3a\u8ba1\u7b97\u673a\u89c6\u89c9\u4e43\u81f3\u4eba\u5de5\u667a\u80fd\u9886\u57df\u6700\u5177\u5b66\u672f\u5f71\u54cd\u529b\u7684\u4e09\u5927\u9876\u4f1a\u4e4b\u4e00\uff0c\u7b2c\u4e00\u5c4a CVPR \u4f1a\u8bae\u8981\u8ffd\u6eaf\u52301983\u5e74\u7f8e\u56fd\u534e\u76db\u987f\uff0c\u81ea\u6b64\u6bcf\u4e00\u5e74\u90fd\u4f1a\u5438\u5f15\u5168\u7403\u7684\u8ba1\u7b97\u673a\u7814\u7a76\u8005\u548c\u884c\u4e1a\u9886\u8896\u6c47\u805a\u4e00\u5802\uff0c\u5171\u540c\u63a2\u8ba8\u8ba1\u7b97\u673a\u89c6\u89c9\u9886\u57df\u6700\u65b0\u7684\u79d1\u5b66\u8fdb\u5c55\u548c\u4ea7\u4e1a\u6210\u679c\u3002<\/p>\n

\u4f5c\u4e3a\u9886\u5148\u7684\u8ba1\u7b97\u673a\u89c6\u89c9\u76db\u4f1a\uff0c\u4f1a\u8bae\u6bcf\u5e74\u90fd\u4f1a\u5f55\u7528\u5f53\u524d\u89c6\u89c9\u9886\u57df\u7684\u6700\u65b0\u7814\u7a76\u3002\u65e9\u57282\u670827\u65e5\uff0cCVPR \u5b98\u7f51\u5c31\u516c\u5e03\u4e86\u4eca\u5e74\u7684\u8bba\u6587\u63a5\u6536\u7ed3\u679c\uff1aCVPR 2024 \u5171\u6709 35691 \u4f4d\u6ce8\u518c\u4f5c\u8005\uff0c11532 \u7bc7\u63d0\u4ea4\u8bba\u6587\uff0c\u5176\u4e2d 2719 \u7bc7\u88ab\u63a5\u6536\uff0c\u5f55\u7528\u7387\u4e3a 23.6%\u3002<\/p>\n

\u4e0e\u4e4b\u76f8\u6bd4\uff0cCVPR 2023 \u5171\u6709 9155 \u7bc7\u8bba\u6587\u88ab\u63d0\u4ea4\uff0c2359 \u7bc7\u8bba\u6587\u88ab\u63a5\u6536\uff0c\u5f55\u7528\u7387\u4e3a 25.8%\u3002\u4eca\u5e74\u7684\u8bba\u6587\u6570\u91cf\u63d0\u9ad8\u4e8620.6%\uff0c\u521b\u4e0b\u65b0\u9ad8\uff0c\u800c\u5f55\u7528\u7387\u964d\u4f4e\u4e86 2.2%\u3002\u53e6\u5916\uff0chightlights \u548c Oral \u4e24\u79cd\u7c7b\u578b\u7684\u8bba\u6587\u5c55\u793a\u5206\u522b\u6709 324 \u7bc7\uff08\u53602.81%\uff09\u548c 90 \u7bc7\uff08\u53600.78%\uff09\u8bba\u6587\u83b7\u9009\uff0c\u7531\u6b64\u53ef\u89c1\uff0c\u672c\u5c4a\u4f1a\u8bae\u7684\u70ed\u5ea6\u3001\u7ade\u4e89\u96be\u5ea6\u4e0e\u5165\u9009\u83b7\u5956\u7684\u542b\u91d1\u91cf\u90fd\u6709\u6240\u4e0a\u5347\u3002<\/p>\n

<\/a><\/p>\n


<\/strong><\/p>\n

CVPR 2024 \u9881\u5956\u73af\u8282<\/strong><\/p>\n

\u5165\u56f4 CVPR 2024 \u51b3\u8d5b\u5708\u7684\u6700\u4f73\u8bba\u6587\u670924\u7bc7\uff0c\u76f8\u6bd4\u53bb\u5e74\u591a\u4e8612\u7bc7\u3002<\/p>\n

<\/a><\/p>\n

AI \u79d1\u6280\u8bc4\u8bba\u68b3\u7406\u4e86\u5019\u9009\u8bba\u6587\u7684\u57fa\u672c\u60c5\u51b5\uff1a<\/p>\n

\u4ece\u5730\u7406\u4f4d\u7f6e\u4e0a\u6765\u770b\uff0c\u4f4d\u5217\u524d\u4e09\u7684\u56fd\u5bb6\u4f9d\u6b21\u4e3a\u7f8e\u56fd\u3001\u4e2d\u56fd\u548c\u5fb7\u56fd\uff1b\u4ece\u7814\u7a76\u9886\u57df\u6765\u770b\uff0c\u4e3b\u8981\u805a\u7126\u5728\u89c6\u89c9\u4e0e\u56fe\u5f62\u3001\u5355\u89c6\u56fe 3D \u91cd\u5efa\u4ee5\u53ca\u56fe\u50cf\u4e0e\u89c6\u9891\u5408\u6210\u7b49\uff1b\u4ece\u4ea7\u4e1a\u754c\u6765\u770b\uff0c\u6709\u4e09\u5bb6\u673a\u6784\u5165\u9009\uff0c\u5206\u522b\u662f NAVER Cloud AI\u3001Google Research \u4ee5\u53ca NVIDIA\uff1b\u4ece\u5b66\u672f\u754c\u6765\u770b\uff0c\u9ad8\u6821\u4f9d\u65e7\u662f\u7814\u7a76\u7684\u4e3b\u8981\u63a8\u52a8\u529b\uff0c\u5176\u4e2d\uff0c\u56fd\u5185\u5165\u9009\u7684\u9ad8\u6821\u6709\u5317\u4eac\u5927\u5b66\u3001\u4e0a\u6d77\u4ea4\u901a\u5927\u5b66\u3001\u4e2d\u5c71\u5927\u5b66\u548c\u6df1\u5733\u5927\u5b66\u3002<\/p>\n

<\/p>\n

\u6700\u4f73\u8bba\u6587<\/p>\n

\u672c\u5c4a CVPR \u603b\u5171\u8bc4\u9009\u51fa 2 \u7bc7\u6700\u4f73\u8bba\u6587\u3002<\/p>\n

\u7b2c\u4e00\u7bc7\u6700\u4f73\u8bba\u6587\u5c5e\u4e8e\u8c37\u6b4c\u7814\u7a76\u9662\u56e2\u961f\u7684\u300aGenerative Image Dynamics \u300b\u3002<\/p>\n

<\/a><\/p>\n

\u8bba\u6587\u94fe\u63a5\uff1ahttps:\/\/arxiv.org\/pdf\/2309.07906<\/p>\n

\u4ee3\u7801\u5730\u5740\uff1ahttp:\/\/generative-dynamics.github.io\/<\/p>\n

\u4f5c\u8005\uff1aZhengqi Li, Richard Tucker, Noah Snavely, Aleksander Holynski<\/p>\n

\u8bba\u6587\u4ecb\u7ecd\uff1a\u672c\u6587\u901a\u8fc7\u4ece\u771f\u5b9e\u89c6\u9891\u4e2d\u63d0\u53d6\u81ea\u7136\u632f\u8361\u52a8\u6001\u7684\u8fd0\u52a8\u8f68\u8ff9\u6765\u5b66\u4e60\u56fe\u50cf\u7a7a\u95f4\u4e2d\u7684\u573a\u666f\u8fd0\u52a8\u5148\u9a8c\u3002\u8be5\u65b9\u6cd5\u5229\u7528\u5085\u91cc\u53f6\u57df\u5bf9\u957f\u671f\u8fd0\u52a8\u8fdb\u884c\u5efa\u6a21\uff0c\u901a\u8fc7\u5355\u56fe\u50cf\u9884\u6d4b\u9891\u8c31\u4f53\u79ef\uff0c\u8fdb\u800c\u751f\u6210\u6574\u4e2a\u89c6\u9891\u7684\u8fd0\u52a8\u7eb9\u7406\uff0c\u53ef\u5e94\u7528\u4e8e\u5c06\u9759\u6001\u56fe\u50cf\u8f6c\u5316\u4e3a\u5faa\u73af\u89c6\u9891\uff0c\u6216\u901a\u8fc7\u56fe\u50cf\u7a7a\u95f4\u6a21\u6001\u57fa\u5b9e\u73b0\u7528\u6237\u4e0e\u771f\u5b9e\u56fe\u50cf\u4e2d\u5bf9\u8c61\u7684\u4ea4\u4e92\uff0c\u6a21\u62df\u5176\u52a8\u6001\u3002<\/p>\n

\u7b2c\u4e8c\u7bc7\u6700\u4f73\u8bba\u6587\u9881\u7ed9\u4e86\u7531\u52a0\u5dde\u5927\u5b66\u5723\u5730\u4e9a\u54e5\u5206\u6821\u3001\u8c37\u6b4c\u7814\u7a76\u9662\u3001\u5357\u52a0\u5dde\u5927\u5b66\u3001\u5251\u6865\u5927\u5b66\u53ca\u5e03\u5170\u8fea\u65af\u5927\u5b66 5 \u6240\u673a\u6784\u5171\u540c\u53d1\u8868\u7684\u300aRich Human Feedback for Text-to-Image Generation \u300b\u3002<\/p>\n

<\/a><\/p>\n

\u8bba\u6587\u94fe\u63a5\uff1ahttps:\/\/arxiv.org\/pdf\/2312.10240<\/p>\n

\u4ee3\u7801\u5730\u5740\uff1ahttps:\/\/github.com\/google-research\/google-research\/tree\/master\/richhf_18k<\/p>\n

\u4f5c\u8005\uff1aYouwei Liang, Junfeng He, Gang Li, Peizhao Li, Arseniy Klimovskiy, Nicholas Carolan, Jiao Sun, Jordi Pont-Tuset, Sarah Young, Feng Yang, Junjie Ke, Krishnamurthy Dj Dvijotham, Katherine M. Collins, Yiwen Luo, Yang Li, Kai J. Kohlhoff, Deepak Ramachandran, Vidhya Navalpakkam<\/p>\n

\u8bba\u6587\u4ecb\u7ecd\uff1a\u8bb8\u591a\u751f\u6210\u7684\u56fe\u50cf\u4ecd\u7136\u5b58\u5728\u8bf8\u5982\u4e0d\u771f\u5b9e\u6027\u3001\u4e0e\u6587\u672c\u63cf\u8ff0\u4e0d\u4e00\u81f4\u4ee5\u53ca\u5ba1\u7f8e\u8d28\u91cf\u4f4e\u7b49\u95ee\u9898\u3002\u672c\u6587\u901a\u8fc7\u9009\u62e9\u9ad8\u8d28\u91cf\u7684\u8bad\u7ec3\u6570\u636e\u8fdb\u884c\u5fae\u8c03\u6765\u6539\u8fdb\u751f\u6210\u6a21\u578b\uff0c\u6216\u8005\u901a\u8fc7\u521b\u5efa\u5e26\u6709\u9884\u6d4b\u70ed\u56fe\u7684\u63a9\u6a21\u6765\u4fee\u590d\u95ee\u9898\u533a\u57df\u3002\u503c\u5f97\u6ce8\u610f\u7684\u662f\uff0c\u8fd9\u4e9b\u6539\u8fdb\u53ef\u4ee5\u63a8\u5e7f\u5230\u7528\u4e8e\u6536\u96c6\u4eba\u7c7b\u53cd\u9988\u6570\u636e\u7684\u56fe\u50cf\u4e4b\u5916\u7684\u6a21\u578b\uff08Muse\uff09\u3002<\/p>\n

\u6700\u4f73\u5b66\u751f\u8bba\u6587<\/p>\n

\u4eca\u5e74\u7684\u6700\u4f73\u5b66\u751f\u8bba\u6587\u540c\u6837\u6709 2 \u7bc7\u5de5\u4f5c\u83b7\u9009\u3002<\/p>\n

\u7b2c\u4e00\u7bc7\u9881\u53d1\u7ed9\u4e86\u6765\u81ea\u5fb7\u56fd\u56fe\u5bbe\u6839\u5927\u5b66\u3001\u56fe\u5bbe\u6839 AI \u4e2d\u5fc3\u3001\u4e0a\u6d77\u79d1\u6280\u5927\u5b66\u53ca\u5e03\u62c9\u683c\u6377\u514b\u6280\u672f\u5927\u5b66\u5171\u540c\u53d1\u8868\u7684\u300aMip-Splatting: Alias-free 3D Gaussian Splatting\u300b\u3002\u503c\u5f97\u6ce8\u610f\u7684\u662f\uff0c\u8be5\u7bc7\u8bba\u6587\u7684\u4e09\u4f4d\u534e\u4eba\u4f5c\u8005\u90fd\u662f\u4e0a\u6d77\u79d1\u6280\u5927\u5b66\u5728\u8bfb\u6216\u6bd5\u4e1a\u7684\u7855\u58eb\u3001\u535a\u58eb\u751f\u3002<\/p>\n

<\/a><\/p>\n

\u8bba\u6587\u94fe\u63a5\uff1ahttps:\/\/arxiv.org\/pdf\/2311.16493<\/p>\n

\u4ee3\u7801\u5730\u5740\uff1ahttps:\/\/github.com\/autonomousvision\/mip-splatting<\/p>\n

\u4f5c\u8005\uff1aZehao Yu , Anpei Chen, Binbin Huang , Torsten Sattler , Andreas Geiger<\/p>\n

\u8bba\u6587\u4ecb\u7ecd\uff1a3D\u9ad8\u65af\u70b9\u67d3\u6280\u672f\u5728\u65b0\u89c6\u89d2\u5408\u6210\u65b9\u9762\u53d6\u5f97\u4e86\u9ad8\u4fdd\u771f\u5ea6\u548c\u6548\u7387\u7684\u6210\u679c\uff0c\u4f46\u5728\u6539\u53d8\u91c7\u6837\u7387\u65f6\u4f1a\u51fa\u73b0\u4f2a\u5f71\u3002\u4e3a\u89e3\u51b3\u8be5\u95ee\u9898\uff0c\u672c\u6587\u5f15\u5165\u4e86\u57fa\u4e8e\u6700\u5927\u91c7\u6837\u9891\u7387\u7684 3D \u5e73\u6ed1\u6ee4\u6ce2\u5668\uff0c\u9650\u5236\u4e86\u9ad8\u65af\u57fa\u5143\u7684\u5927\u5c0f\uff0c\u6d88\u9664\u4e86\u653e\u5927\u65f6\u7684\u9ad8\u9891\u4f2a\u5f71\u3002\u540c\u65f6\uff0c\u7528 2D Mip \u6ee4\u6ce2\u5668\u66ff\u4ee3 2D \u81a8\u80c0\uff0c\u6a21\u62df 2D \u76d2\u6ee4\u6ce2\u5668\uff0c\u51cf\u8f7b\u4e86\u6df7\u53e0\u548c\u81a8\u80c0\u95ee\u9898\u3002\u8bc4\u4f30\u7ed3\u679c\u663e\u793a\uff0c\u5728\u5355\u5c3a\u5ea6\u8bad\u7ec3\u548c\u591a\u5c3a\u5ea6\u6d4b\u8bd5\u4e0b\uff0c\u8be5\u65b9\u6cd5\u6709\u6548\u3002<\/p>\n

\u7b2c\u4e8c\u7bc7\u6700\u4f73\u5b66\u751f\u8bba\u6587\u9881\u53d1\u7ed9\u4e86\u6765\u81ea\u7f8e\u56fd\u4fc4\u4ea5\u4fc4\u5dde\u7acb\u5927\u5b66\u3001\u5fae\u8f6f\u7814\u7a76\u9662\u3001\u52a0\u5dde\u5927\u5b66\u6b27\u6587\u5206\u6821\u3001\u4f26\u65af\u52d2\u7406\u5de5\u5b66\u9662\u5171\u540c\u53d1\u5e03\u7684\u300aBioCLlP: A Vision Foundation Model for the Tree of Life\u300b\u3002<\/p>\n

<\/a><\/p>\n

\u8bba\u6587\u94fe\u63a5\uff1ahttps:\/\/arxiv.org\/abs\/2311.18803<\/p>\n

\u4ee3\u7801\u5730\u5740\uff1ahttps:\/\/imageomics.github.io\/bioclip\/<\/p>\n

\u4f5c\u8005\uff1aSamuel Stevens, Jiaman (Lisa) Wu, Matthew J Thompson, Elizabeth G Campolongo, Chan Hee (Luke) Song, David Edward Carlyn, Li Dong, Wasila M Dahdul, Charles Stewart, Tanya Berger-Wolf, Wei-Lun (Harry) Chao, Yu Su<\/p>\n

\u8bba\u6587\u4ecb\u7ecd\uff1a\u81ea\u7136\u754c\u56fe\u50cf\u7684\u4e30\u5bcc\u6027\u4e3a\u751f\u7269\u4fe1\u606f\u5b66\u63d0\u4f9b\u4e86\u5b9d\u8d35\u6570\u636e\u6e90\u3002\u5c3d\u7ba1\u9488\u5bf9\u7279\u5b9a\u4efb\u52a1\u7684\u8ba1\u7b97\u65b9\u6cd5\u548c\u5de5\u5177\u4e0d\u65ad\u6d8c\u73b0\uff0c\u4f46\u5b83\u4eec\u901a\u5e38\u4e0d\u6613\u9002\u5e94\u65b0\u95ee\u9898\u6216\u6269\u5c55\u5230\u4e0d\u540c\u80cc\u666f\u548c\u6570\u636e\u96c6\u3002\u4e3a\u5e94\u5bf9\u8fd9\u4e00\u6311\u6218\uff0c\u672c\u6587\u521b\u5efa\u4e86 TreeOfLife-10M \u6570\u636e\u96c6\uff0c\u8fd9\u662f\u8fc4\u4eca\u4e3a\u6b62\u6700\u5927\u548c\u6700\u591a\u6837\u5316\u7684\u751f\u7269\u56fe\u50cf\u6570\u636e\u96c6\u3002BioCLIP \u6a21\u578b\u57fa\u4e8e\u751f\u547d\u6811\u6784\u5efa\uff0c\u5229\u7528 TreeOfLife-10M \u7684\u591a\u6837\u5316\u751f\u7269\u56fe\u50cf\u548c\u7ed3\u6784\u5316\u77e5\u8bc6\uff0c\u5c55\u73b0\u51fa\u5728\u7ec6\u7c92\u5ea6\u751f\u7269\u5206\u7c7b\u4efb\u52a1\u4e2d\u7684\u5353\u8d8a\u6027\u80fd\uff0c\u663e\u8457\u8d85\u8d8a\u73b0\u6709\u57fa\u7ebf\u65b9\u6cd5\uff0c\u5176\u5185\u5728\u8bc4\u4f30\u63ed\u793a\u4e86 BioCLIP \u7684\u5f3a\u6cdb\u5316\u80fd\u529b\u3002<\/p>\n

\u5176\u4ed6\u5956\u9879<\/p>\n

\u672c\u5c4a\u9ec4\u7166\u6d9b\u7eaa\u5ff5\u5956\u7531 Andrea Vedaldi \u83b7\u5f97\u3002<\/p>\n

<\/a><\/p>\n

Andrea Vedaldi \u662f\u725b\u6d25\u5927\u5b66\u8ba1\u7b97\u673a\u89c6\u89c9\u548c\u673a\u5668\u5b66\u4e60\u6559\u6388\uff0c\u4e5f\u662f VGG\uff08\u89c6\u89c9\u51e0\u4f55\uff09\u7ec4\u7684\u6210\u5458\u3002\u4ed6\u7684\u7814\u7a76\u91cd\u70b9\u5728\u4e8e\u5f00\u53d1\u8ba1\u7b97\u673a\u89c6\u89c9\u548c\u673a\u5668\u5b66\u4e60\u65b9\u6cd5\uff0c\u4ee5\u81ea\u52a8\u7406\u89e3\u56fe\u50cf\u548c\u89c6\u9891\u5185\u5bb9\u3002\u6b64\u5916\uff0c\u4ed6\u8fd8\u5728 2012 \u5e74\u81f3 2023 \u5e74\u671f\u95f4\u62c5\u4efb Facebook AI Research\uff08FAIR\uff09\u7684\u7814\u7a76\u79d1\u5b66\u5bb6\uff0c\u5e76\u57282023\u5e74\u6210\u4e3a Meta AI \u7684\u7814\u7a76\u79d1\u5b66\u5bb6\u3002<\/p>\n

<\/p>\n

\u56fe\u50cf\u89c6\u9891\u751f\u6210\u5360\u9886C\u4f4d<\/strong><\/p>\n

\u4ece\u8fd1\u671f\u4e54\u6cbb\u4e9a\u7406\u5de5\u5b66\u9662\u8ba1\u7b97\u673a\u5b66\u9662\uff08College of Computing, Georgia Institute of Technology\uff09\u5bf9 CVPR 2024 \u5f55\u7528\u6570\u636e\u7684\u7edf\u8ba1\u5206\u6790\u6765\u770b\uff0c\u8bba\u6587\u4e3b\u8981\u6db5\u76d636\u4e2a\u4e3b\u9898\u9886\u57df\uff0c\u6392\u540d\u524d\u5341\u7684\u4e3b\u9898\u5206\u522b\u662f\uff1a\u56fe\u50cf\u548c\u89c6\u9891\u5408\u6210\u4e0e\u751f\u6210\uff0c\u4e09\u7ef4\u89c6\u89c9\uff0c\u4eba\u4f53\u884c\u4e3a\u8bc6\u522b\uff0c\u89c6\u89c9\u3001\u8bed\u8a00\u4e0e\u8bed\u8a00\u63a8\u7406\uff0c\u5e95\u5c42\u89c6\u89c9\uff0c\u8bc6\u522b\uff08\u5206\u7c7b\u3001\u68c0\u6d4b\u3001\u68c0\u7d22\uff09\uff0c\u8fc1\u79fb\u5b66\u4e60\u4e0e\u591a\u6a21\u6001\u5b66\u4e60\u3002<\/p>\n

\u5176\u4e2d\uff0c\u9664\u4e86\u81ea\u52a8\u9a7e\u9a76\u4e0e\u4e09\u7ef4\u89c6\u89c9\u8fd9\u4e24\u4f4d\u70ed\u70b9\u5e38\u5ba2\u5916\uff0c\u4eca\u5e74\u6392\u5728\u9996\u4f4d\u7684\u5173\u952e\u8bcd\u662f\u56fe\u50cf\u548c\u89c6\u9891\u5408\u6210\u4e0e\u751f\u6210\uff08Image and video synthesis and generation\uff09\uff0c\u603b\u8ba1\u6709 329 \u7bc7\u8bba\u6587\uff0c\u6210\u4e3a\u4e86\u4eca\u5e74 CVPR \u6700\u706b\u7684\u7814\u7a76\u4e3b\u9898\u3002<\/p>\n

\u70ed\u95e8\u4e3b\u9898\u4ece\u53bb\u5e74\u7684\u6269\u6563\u6a21\u578b\uff08Diffusion models\uff09\u8f6c\u53d8\u4e3a\u4eca\u5e74\u7684\u56fe\u50cf\u548c\u89c6\u9891\u5408\u6210\u4e0e\u751f\u6210\uff0c\u4e5f\u540c Sora \u5728\u6625\u8282\u6253\u54cd\u7684\u5f00\u95e8\u70ae\u9065\u76f8\u547c\u5e94\u3002<\/p>\n

\u5728\u88ab CVPR \u63a5\u6536\u7684\u56fe\u50cf\u548c\u89c6\u9891\u5408\u6210\u4e0e\u751f\u6210\u76f8\u5173\u8bba\u6587\u4e2d\uff0c\u6709\u4e0d\u5c11\u8fc7\u53bb\u51e0\u4e2a\u6708\u4ee4\u4eba\u60ca\u8273\u7684\u65b0\u79d1\u7814\u6210\u679c\u6216\u4ea7\u54c1\uff0c\u6bd4\u5982\u8c37\u6b4c DeepMind \u548c\u7814\u7a76\u9662\u53d1\u5e03\u7684 Instruct-Imagen\u3002<\/p>\n

Instruct-Imagen \u662f\u4e00\u4e2a\u80fd\u591f\u5904\u7406\u5f02\u6784\u56fe\u50cf\u751f\u6210\u4efb\u52a1\u5e76\u5728\u672a\u89c1\u8fc7\u7684\u4efb\u52a1\u4e0a\u6cdb\u5316\u7684\u6a21\u578b\u3002\u6709\u8da3\u7684\u662f\uff0c\u8c37\u6b4c\u56e2\u961f\u5f15\u5165\u4e86\u591a\u6a21\u6001\u6307\u4ee4\u751f\u6210\u56fe\u50cf\u7684\u4efb\u52a1\u8868\u793a\uff0c\u4ee5\u7cbe\u786e\u5730\u8868\u8fbe\u4e00\u7cfb\u5217\u751f\u6210\u610f\u56fe\uff0c\u5e76\u4f7f\u7528\u81ea\u7136\u8bed\u8a00\u5c06\u4e0d\u540c\u7684\u6a21\u6001\uff08\u4f8b\u5982\u6587\u672c\u3001\u8fb9\u7f18\u3001\u98ce\u683c\u3001\u4e3b\u9898\u7b49\uff09\u878d\u5408\u8d77\u6765\uff0c\u4f7f\u5f97\u4e30\u5bcc\u7684\u751f\u6210\u610f\u56fe\u53ef\u4ee5\u5728\u7edf\u4e00\u7684\u683c\u5f0f\u4e2d\u6807\u51c6\u5316\u3002<\/p>\n

<\/a><\/p>\n

\u534e\u4e1c\u7406\u5de5\u5927\u5b66\u63d0\u51fa\u7684 DisenDiff \u6ce8\u610f\u6821\u51c6\u673a\u5236\u4e5f\u88ab\u9009\u4e3a Oral \u6587\u7ae0\uff0c\u4ed6\u4eec\u7684\u5de5\u4f5c\u65e8\u5728\u89e3\u51b3\u73b0\u6709\u7684\u6587\u672c\u5230\u56fe\u50cf\uff08T2I\uff09\u6a21\u578b\u5728\u4e2a\u6027\u5316\u5b9a\u5236\u65f6\u65e0\u6cd5\u4fdd\u6301\u89c6\u89c9\u4e00\u81f4\u6027\u548c\u6982\u5ff5\u4ea4\u53c9\u5f71\u54cd\u7684\u95ee\u9898\u3002<\/p>\n

\u8be5\u65b9\u6cd5\u901a\u8fc7\u5f15\u5165\u4e0e\u7c7b\u522b\u7ed1\u5b9a\u7684\u5b66\u4e60\u578b\u4fee\u9970\u7b26\u6765\u6355\u6349\u591a\u4e2a\u6982\u5ff5\u7684\u5c5e\u6027\uff0c\u5e76\u5728\u4ea4\u53c9\u6ce8\u610f\u529b\u64cd\u4f5c\u6fc0\u6d3b\u540e\u5206\u79bb\u548c\u52a0\u5f3a\u7c7b\u522b\uff0c\u4ee5\u786e\u4fdd\u6982\u5ff5\u7684\u5168\u9762\u6027\u548c\u72ec\u7acb\u6027\u3002\u6b64\u5916\uff0c\u901a\u8fc7\u6291\u5236\u4e0d\u540c\u7c7b\u522b\u7684\u6ce8\u610f\u529b\u6fc0\u6d3b\u6765\u51cf\u5c11\u6982\u5ff5\u95f4\u7684\u76f8\u4e92\u5f71\u54cd\u3002<\/p>\n

\u5b9e\u9a8c\u7ed3\u679c\u8868\u660e\uff0cDisenDiff \u5728\u5b9a\u6027\u548c\u5b9a\u91cf\u8bc4\u4f30\u4e2d\u5747\u4f18\u4e8e\u73b0\u6709\u6280\u672f\uff0c\u5e76\u80fd\u4e0e LoRA \u548c\u4fee\u590d\u7ba1\u9053\u517c\u5bb9\uff0c\u63d0\u4f9b\u66f4\u4e30\u5bcc\u7684\u4ea4\u4e92\u4f53\u9a8c\u3002<\/p>\n

<\/a><\/p>\n

\u6269\u6563\u6a21\u578b\u5728\u5f53\u4e0b\u53ef\u4ee5\u8bf4\u4e3b\u5bfc\u4e86\u56fe\u50cf\u751f\u6210\u8fd9\u4e2a\u9886\u57df\uff0c\u4e5f\u5bf9\u4e8e\u5927\u6570\u636e\u96c6\u5c55\u73b0\u51fa\u4e86\u5f3a\u5927\u7684\u7f29\u653e\u6027\uff0c\u7531 NVIDIA \u548c Aalto University \u7684\u7814\u7a76\u4eba\u5458\u64b0\u5199\u7684\u300aAnalyzing and Improving the Training Dynamics of Diffusion Models\u300b\uff0c\u5173\u6ce8\u70b9\u5728\u4e8e\u6539\u8fdb\u6269\u6563\u6a21\u578b\u7684\u8bad\u7ec3\u52a8\u6001\u3002<\/p>\n

\u8be5\u7bc7\u7814\u7a76\u8005\u5728\u4e0d\u6539\u53d8 high-level \u67b6\u6784\u7684\u524d\u63d0\u4e0b\uff0c\u8bc6\u522b\u548c\u7ea0\u6b63\u4e86\u6d41\u884c\u7684 ADM \u6269\u6563\u6a21\u578b\u4e2d\u7684\u51e0\u4e2a\u8bad\u7ec3\u65b9\u9762\u4e0d\u5747\u5300\u7684\u539f\u56e0\u3002\u628a ImageNet 512\u00d7512 \u56fe\u50cf\u751f\u6210\u4efb\u52a1\u7684 FID \u7531\u539f\u6765\u7684 2.41 \u964d\u4f4e\u5230\u4e86 1.81\uff0c\u8fd9\u662f\u4e00\u4e2a\u8861\u91cf\u751f\u6210\u56fe\u50cf\u8d28\u91cf\u7684\u91cd\u8981\u6307\u6807\uff0c\u5c06\u751f\u6210\u8d28\u91cf\u548c\u6a21\u578b\u590d\u6742\u5ea6\u53d8\u5f97\u53ef\u89c6\u5316\u3002<\/p>\n

<\/a><\/p>\n

\u7814\u7a76\u8005\u8fd8\u63d0\u51fa\u4e86\u4e00\u79cd\u5728\u8bad\u7ec3\u5b8c\u6210\u540e\u8bbe\u7f6eEMA\u53c2\u6570\u7684\u65b9\u6cd5\uff0c\u5141\u8bb8\u5728\u4e0d\u589e\u52a0\u591a\u6b21\u8bad\u7ec3\u6210\u672c\u7684\u60c5\u51b5\u4e0b\u7cbe\u786e\u8c03\u6574EMA\u957f\u5ea6\uff0c\u5e76\u63ed\u793a\u4e86\u5176\u4e0e\u7f51\u7edc\u67b6\u6784\u3001\u8bad\u7ec3\u65f6\u95f4\u548c\u5f15\u5bfc\u7684\u60ca\u4eba\u4ea4\u4e92\u4f5c\u7528\u3002<\/p>\n

\u8fd9\u4e9b\u7a81\u7834\u6027\u7684\u7814\u7a76\uff0c\u9884\u793a\u7740\u4eba\u5de5\u667a\u80fd\u5728\u56fe\u50cf\u751f\u6210\u9886\u57df\uff0c\u6b63\u5728\u4ee5\u524d\u6240\u672a\u6709\u7684\u901f\u5ea6\u91cd\u5851\u827a\u672f\u521b\u4f5c\u548c\u89c6\u89c9\u4e0a\u5185\u5bb9\u751f\u4ea7\u7684\u8fb9\u754c\u3002<\/p>\n

\u503c\u5f97\u4e00\u63d0\u7684\u662f\uff0c\u4eca\u5e74\u6070\u597d\u662f\u751f\u6210\u5bf9\u6297\u7f51\u7edc\uff08GANs\uff09\u8bde\u751f\u7684\u5341\u5468\u5e74\u30022014\u5e74\uff0cIan Goodfellow \u7b49\u4eba\u63d0\u51fa\u4e86\u6df1\u5ea6\u5b66\u4e60\u9886\u57df\u7684\u6b64\u9879\u91cc\u7a0b\u7891\u6280\u672f\uff0c\u4e0d\u4ec5\u5f00\u8f9f\u4e86\u751f\u6210\u5f0f\u6a21\u578b\u7684\u65b0\u9886\u57df\uff0c\u800c\u4e14\u5bf9\u65e0\u76d1\u7763\u5b66\u4e60\u4ea7\u751f\u4e86\u6df1\u8fdc\u5f71\u54cd\u3002<\/p>\n

<\/p>\n

\u89c6\u89c9\u57fa\u7840\u6a21\u578b\u70b9\u71c3\u73b0\u573a<\/strong><\/p>\n

\u57fa\u4e8e Transformer\uff0c\u4ee5\u53ca\u53d7\u5230\u8bed\u8a00\u5927\u6a21\u578b\u7684\u542f\u53d1\uff0c\u8ba1\u7b97\u673a\u89c6\u89c9\u9886\u57df\u5728 2023 \u5e74\u4ee5\u6765\u5bf9\u89c6\u89c9\u57fa\u7840\u6a21\u578b\uff08VFM\uff09\u7684\u7814\u7a76\u70ed\u60c5\u9ad8\u6da8\u3002<\/p>\n

\u89c6\u89c9\u57fa\u7840\u6a21\u578b (VFM)\uff0c\u4e00\u822c\u5728\u7279\u5b9a\u7684\u9886\u57df\uff0c\u50cf\u56fe\u50cf\u5206\u7c7b\u3001\u76ee\u6807\u68c0\u6d4b\u548c\u56fe\u50cf\u751f\u6210\u7b49\u4f17\u591a\u4e0b\u6e38\u4efb\u52a1\u4e2d\u8868\u73b0\u7a81\u51fa\u3002\u4f8b\u5982\uff0c\u591a\u6a21\u6001 CLIP \u6a21\u578b\u64c5\u957f\u96f6\u6837\u672c\u89c6\u89c9\u8bed\u8a00\u7406\u89e3\uff0c\u81ea\u76d1\u7763\u5b66\u4e60\u6a21\u578bDINOv2 \u64c5\u957f\u8bed\u4e49\u5206\u5272\uff0c\u81ea\u76d1\u7763\u5b66\u4e60\u65b9\u6cd5SAM \u64c5\u957f\u5f00\u653e\u8bcd\u6c47\u5b9e\u4f8b\u5206\u5272\u3002<\/p>\n

CVPR 2024 \u5171\u6709 123 \u4e2a workshop \u4e0e 24 \u573a tutorial\uff0c\u5728\u8fd9\u4e2a\u5e74\u5ea6\u76db\u4f1a\u7684\u73b0\u573a\uff0cAI \u79d1\u6280\u8bc4\u8bba\u89c2\u5bdf\u5230\uff1a\u5c3d\u7ba1\u89c6\u89c9\u57fa\u7840\u6a21\u578b\u7684\u76f8\u5173\u5de5\u4f5c\u5728\u88ab\u63a5\u6536\u8bba\u6587\u6570\u91cf\u4e2d\u7684\u5360\u6bd4\u4e0d\u5927\uff0c\u4f46\u8d85\u8fc7 10 \u573a\u7814\u8ba8\u4f1a\u4ee5\u89c6\u89c9\u57fa\u7840\u6a21\u578b\u4e3a\u4e3b\u9898\uff0c\u5f00\u5c55\u4e86\u5b66\u4e60\u548c\u5e94\u7528\u89c6\u89c9\u57fa\u7840\u6a21\u578b\u6700\u524d\u6cbf\u65b9\u6cd5\u7684\u8ba8\u8bba\u3002<\/p>\n

\u6bd4\u5982 6 \u6708 17 \u65e5\u4e3e\u884c\u7684\u7b2c\u4e8c\u5c4a\u57fa\u7840\u6a21\u578b\u7814\u8ba8\u4f1a\u4e0a\uff0c\u4e0e\u4f1a\u8005\u5206\u4eab\u4e86\u89c6\u89c9\u57fa\u7840\u6a21\u578b\u548c\u5927\u8bed\u8a00\u6a21\u578b\u7684\u7406\u8bba\u6d1e\u5bdf\u3001\u9ad8\u6548\u67b6\u6784\u8bbe\u8ba1\u4ee5\u53ca\u5377\u79ef\u548c\u56fe\u6df7\u5408\u7f51\u7edc\u8bbe\u8ba1\u7684\u7814\u7a76\uff0c\u5e76\u63a2\u8ba8\u4e86\u5728\u56fe\u50cf\u548c\u89c6\u9891\u751f\u6210\u3001\u4e0d\u540c\u76d1\u7763\u5b66\u4e60\u8bbe\u7f6e\u3001\u591a\u6a21\u6001\u6a21\u578b\u7b49\uff0c\u8fd8\u8ba8\u8bba\u4e86\u5982\u4f55\u5c06\u57fa\u7840\u6a21\u578b\u7684\u524d\u6cbf\u7814\u7a76\u6210\u679c\u5e94\u7528\u4e8e\u533b\u7597\u3001\u5730\u7403\u79d1\u5b66\u3001\u9065\u611f\u3001\u751f\u7269\u3001\u519c\u4e1a\u548c\u6c14\u5019\u79d1\u5b66\u7b49\u591a\u4e2a\u9886\u57df\uff0c\u4ee5\u5f25\u5408\u7814\u7a76\u4e0e\u5b9e\u9645\u5e94\u7528\u4e4b\u95f4\u7684\u5dee\u8ddd\u3002<\/p>\n

<\/a><\/p>\n

\u5728\u300c\u89c6\u89c9\u57fa\u7840\u6a21\u578b\u6700\u65b0\u8fdb\u5c55\u300d\u7684\u5206\u4eab\u4f1a\u4e2d\uff0c\u5609\u5bbe\u4eec\u8ba8\u8bba\u4e86\u7528\u4e8e\u591a\u6a21\u6001\u7406\u89e3\u548c\u751f\u6210\u7684\u89c6\u89c9\u57fa\u7840\u6a21\u578b\uff0c\u57fa\u51c6\u6d4b\u8bd5\u548c\u8bc4\u4f30\u89c6\u89c9\u57fa\u7840\u6a21\u578b\uff0c\u4ee5\u53ca\u57fa\u4e8e\u89c6\u89c9\u57fa\u7840\u6a21\u578b\u7684\u667a\u80fd\u4f53\u548c\u5176\u4ed6\u9ad8\u7ea7\u7cfb\u7edf\u3002<\/p>\n

<\/a><\/p>\n<\/p>\n

\u5206\u4eab\u5609\u5bbe\uff1aTiktok-Chunyuan Li<\/p>\n

\u81ea 2020 \u5e74\u5f15\u5165\u89c6\u89c9 Transformers\uff08ViT\uff09\u4ee5\u6765\uff0c\u8ba1\u7b97\u673a\u89c6\u89c9\u754c\u89c1\u8bc1\u4e86\u57fa\u4e8e Transformer \u7684\u8ba1\u7b97\u673a\u89c6\u89c9\u6a21\u578b\u7684\u7206\u70b8\u6027\u589e\u957f\uff0c\u5176\u5e94\u7528\u8303\u56f4\u4ece\u56fe\u50cf\u5206\u7c7b\u5230\u5bc6\u96c6\u9884\u6d4b\uff08\u5982\u76ee\u6807\u68c0\u6d4b\u3001\u5206\u5272\uff09\u3001\u89c6\u9891\u3001\u81ea\u76d1\u7763\u5b66\u4e60\u30013D\u548c\u591a\u6a21\u6001\u5b66\u4e60\u3002<\/p>\n

\u56e0\u6b64\uff0cCVPR 2024 \u4e2d\u7684\u7b2c\u4e09\u5c4a\u89c6\u89c9 Transformer \u7814\u8ba8\u4f1a\u5c06\u4f1a\u8bae\u91cd\u70b9\u653e\u5728\u4e86\u4e3a\u89c6\u89c9\u4efb\u52a1\u8bbe\u8ba1 Transformer \u6a21\u578b\u7684\u673a\u9047\u548c\u5176\u5f00\u653e\u6027\u6311\u6218\u4e4b\u4e2d\u3002<\/p>\n

\u673a\u5668\u9057\u5fd8\uff08Machine Unlearning\uff0c\u4e5f\u79f0\u9057\u5fd8\u5b66\u4e60\uff09\u5bf9\u57fa\u7840\u6a21\u578b\u7684\u91cd\u8981\u6027\u540c\u6837\u4e0d\u8a00\u800c\u55bb\uff0c\u4e13\u6ce8\u4e8e\u4ece\u9884\u8bad\u7ec3\u6a21\u578b\u4e2d\u5254\u9664\u90a3\u4e9b\u4e0d\u518d\u9700\u8981\u7684\u6570\u636e\uff0c\u5982\u4e2a\u4eba\u9690\u79c1\u4fe1\u606f\u6216\u8fdd\u53cd\u6cd5\u89c4\u7684\u6570\u636e\uff0c\u5e76\u786e\u4fdd\u6a21\u578b\u7ee7\u7eed\u53d1\u6325\u5176\u5e94\u6709\u7684\u529f\u80fd\u800c\u4e0d\u53d7\u5f71\u54cd\uff0c\u56e0\u6b64 CVPR 2024 \u4e2d\u4e5f\u6709\u7814\u8ba8\u4f1a\u96c6\u4e2d\u8ba8\u8bba\u89c6\u89c9\u57fa\u7840\u6a21\u578b\u4e2d\u673a\u5668\u9057\u5fd8\u7684\u8fd0\u7528\u3002<\/p>\n

\u800c 3D \u57fa\u7840\u6a21\u578b\u7684\u53d1\u5c55\u6b63\u6210\u4e3a\u81ea\u7136\u8bed\u8a00\u5904\u7406\u548c 2D \u89c6\u89c9\u4e4b\u540e\u7684\u53c8\u4e00\u573a\u6280\u672f\u9769\u547d\uff0c\u9884\u793a\u7740\u5728 3D \u5185\u5bb9\u521b\u4f5c\u3001AR\/VR\u3001\u673a\u5668\u4eba\u6280\u672f\u548c\u81ea\u52a8\u9a7e\u9a76\u7b49\u9886\u57df\u7684\u5e7f\u6cdb\u5e94\u7528\u524d\u666f\u3002CVPR 2024 \u7684\u7814\u8ba8\u4f1a\u8fd8\u9080\u8bf7\u4e86 3D \u89c6\u89c9\u9886\u57df\u7684\u4e13\u5bb6\uff0c\u5171\u540c\u63a2\u8ba8 3D \u57fa\u7840\u6a21\u578b\u7684\u6784\u5efa\uff0c\u5305\u62ec\u6570\u636e\u96c6\u7684\u9009\u62e9\u3001\u6a21\u578b\u5e94\u9488\u5bf9\u76843D\u4efb\u52a1\u3001\u67b6\u6784\u5171\u8bc6\u4ee5\u53ca\u6f5c\u5728\u5e94\u7528\u3002<\/p>\n

\u6b64\u5916\uff0c\u57fa\u7840\u6a21\u578b\u8fd8\u88ab\u89c6\u4e3a\u6784\u5efa\u66f4\u901a\u7528\u81ea\u4e3b\u7cfb\u7edf\u7684\u65b0\u8def\u5f84\uff0c\u56e0\u5176\u80fd\u591f\u4ece\u5927\u91cf\u6570\u636e\u4e2d\u5b66\u4e60\u5e76\u6cdb\u5316\u5230\u65b0\u4efb\u52a1\u3002CVPR 2024 \u4e2d\u6709\u7814\u8ba8\u4f1a\u5173\u6ce8\u81ea\u4e3b\u7cfb\u7edf\uff0c\u63a2\u7a76\u57fa\u7840\u6a21\u578b\u5bf9\u81ea\u4e3b\u4ee3\u7406\u7684\u6f5c\u529b\uff0c\u4e0e\u4f1a\u8005\u4eec\u8ba4\u4e3a\u672a\u6765\u5728\u4e8e\u53ef\u89e3\u91ca\u7684\u3001\u7aef\u5230\u7aef\u7684\u6a21\u578b\uff0c\u8fd9\u4e9b\u6a21\u578b\u80fd\u591f\u7406\u89e3\u4e16\u754c\u5e76\u6cdb\u5316\u5230\u672a\u8bbf\u95ee\u7684\u73af\u5883\u4e2d\u3002<\/p>\n

CVPR 2024 \u7684\u73b0\u573a\u4e2d\u8fd8\u6709\u7814\u8ba8\u4f1a\u63a2\u8ba8\u4e86\u5bf9\u6297\u6027\u673a\u5668\u5b66\u4e60\u7684\u6700\u65b0\u8fdb\u5c55\u548c\u6311\u6218\uff0c\u91cd\u70b9\u5173\u6ce8\u57fa\u7840\u6a21\u578b\u7684\u9c81\u68d2\u6027\uff0c\u8be5 workshop \u8fd8\u7ec4\u7ec7\u4e86\u4e00\u573a\u9488\u5bf9\u57fa\u7840\u6a21\u578b\u7684\u5bf9\u6297\u6027\u653b\u51fb\u6311\u6218\u3002<\/p>\n

\u6709\u7684\u7814\u8ba8\u4f1a\u5219\u805a\u7126\u4e8e\u533b\u5b66\u6210\u50cf\u9886\u57df\u57fa\u7840\u6a21\u578b\u7684\u96c6\u6210\u548c\u5e94\u7528\uff0c\u8ba8\u8bba\u6db5\u76d6\u4e86\u5404\u79cd\u533b\u5b66\u6570\u636e\u7684\u6700\u65b0\u6280\u672f\uff0c\u5982\u8d85\u58f0\u5fc3\u52a8\u56fe\u3001\u773c\u5e95\u3001\u75c5\u7406\u5b66\u548c\u653e\u5c04\u5b66\uff0c\u4ee5\u53ca\u5728\u4e34\u5e8a\u73af\u5883\u4e2d\u4f7f\u7528\u57fa\u7840\u6a21\u578b\u7684\u5b9e\u9645\u6311\u6218\u3002<\/p>\n

<\/p>\n

\u5199\u5728\u6700\u540e<\/strong><\/p>\n

\u4e24\u5929\u524d\uff0cRunway \u65f6\u9694\u4e00\u5e74\u63a8\u51fa Gen-3 Alpha\uff0c\u5ba3\u5e03\u89c6\u9891\u751f\u6210\u8d5b\u9053\u738b\u8005\u5f52\u6765\u3002\u5728 CVPR 2024 \u7684\u73b0\u573a\uff0cAI \u79d1\u6280\u8bc4\u8bba\u4e5f\u542c\u5230\u4e86\u5173\u4e8e GPT-5 \u6216\u4e8e 3 \u4e2a\u6708\u540e\u53d1\u5e03\u7684\u6d88\u606f\uff0c\u4e1a\u5185\u5bf9\u5176\u63a8\u7406\u80fd\u529b\u4e0e\u591a\u6a21\u6001\u80fd\u529b\u66f4\u662f\u62a5\u4ee5\u671f\u5f85\u3002<\/p>\n

\u90a3\u4e48\uff0c\u8ba1\u7b97\u673a\u89c6\u89c9\u8fd8\u6709\u54ea\u4e9b\u70ed\u70b9\u4f1a\u662f\u672a\u6765\u8d8b\u52bf\uff1f\u56fe\u50cf\u3001\u89c6\u9891\u751f\u6210\u4e0e\u89c6\u89c9\u57fa\u7840\u6a21\u578b\u7684\u4e0b\u4e00\u6b65\u53d1\u5c55\u5728\u54ea\u91cc\uff1f3D \u89c6\u89c9\u3001\u81ea\u52a8\u9a7e\u9a76\u7b49\u5f80\u5c4a\u300c\u82b1\u65e6\u300d\u53c8\u6709\u4f55\u65b0\u52a8\u6001\uff1f\u673a\u5668\u4eba\u4e0e\u5177\u8eab\u667a\u80fd\u6709\u65e0\u65b0\u4eae\u70b9\uff1f<\/p>\n

\u8ba9\u6211\u4eec\u4e00\u8d77\u671f\u5f85\uff0cCVPR 2024 \u7684\u7cbe\u5f69\u4ecd\u5728\u7ee7\u7eed\u3002<\/p>\n

<\/p>\n

\u672c\u6587\u96f7\u5cf0\u7f51(\u516c\u4f17\u53f7\uff1a\u96f7\u5cf0\u7f51)<\/span>\u4f5c\u8005 anna042023 \u5c06\u6301\u7eed\u5173\u6ce8AI\u5927\u6a21\u578b\u9886\u57df\u7684\u4eba\u4e8b\u3001\u4f01\u4e1a\u3001\u5546\u4e1a\u5e94\u7528\u4ee5\u53ca\u884c\u4e1a\u53d1\u5c55\u8d8b\u52bf\uff0c\u6b22\u8fce\u6dfb\u52a0\u4ea4\u6d41\uff0c\u4e92\u901a\u6709\u65e0\u3002\u96f7\u5cf0\u7f51<\/span><\/p>\n

<\/p>\n

\u96f7\u5cf0\u7f51\u539f\u521b\u6587\u7ae0\uff0c\u672a\u7ecf\u6388\u6743\u7981\u6b62\u8f6c\u8f7d\u3002\u8be6\u60c5\u89c1\u8f6c\u8f7d\u987b\u77e5<\/a>\u3002<\/p>\n

\n
\n <\/a>
\n <\/a>\n <\/p>\n

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