{"id":1171,"date":"2024-04-25T00:21:24","date_gmt":"2024-04-25T00:21:24","guid":{"rendered":"https:\/\/www.gdsig.cn\/?gdsig=272"},"modified":"2024-04-25T00:21:24","modified_gmt":"2024-04-25T00:21:24","slug":"post-272","status":"publish","type":"post","link":"https:\/\/test.gdsig.cn\/index.php\/2024\/04\/25\/post-272\/","title":{"rendered":"\u4f1a\u8bae\u9884\u544a\uff1a\u5e7f\u4e1c\u7701CVPR 2024\u8bba\u6587\u5206\u4eab\u5b66\u672f\u62a5\u544a\u4f1a"},"content":{"rendered":"

\"\u5fae\u4fe1\u56fe\u7247_20240425002214.jpg\"<\/p>\n

<\/p>\n


<\/span><\/p>\n

<\/span><\/p>\n

<\/span><\/p>\n

\u4e3b\u529e\uff1a<\/span><\/strong><\/span><\/p>\n

\u5e7f\u4e1c\u7701\u56fe\u8c61\u56fe\u5f62\u5b66\u4f1a\uff08GDSIG\uff09<\/span><\/p>\n

\u627f\u529e\uff1a<\/span><\/strong><\/span><\/strong><\/span><\/p>\n

\u534e\u5357\u7406\u5de5\u5927\u5b66\u7535\u5b50\u4e0e\u4fe1\u606f\u5b66\u9662<\/span><\/p>\n

\u4e2d\u5c71\u5927\u5b66\u8ba1\u7b97\u673a\u5b66\u9662<\/span><\/p>\n

\u6df1\u5733\u5927\u5b66\u7535\u5b50\u4e0e\u4fe1\u606f\u5de5\u7a0b\u5b66\u9662<\/span><\/p>\n

\u5357\u65b9\u79d1\u6280\u5927\u5b66\u8ba1\u7b97\u673a\u79d1\u5b66\u4e0e\u5de5\u7a0b\u5b66\u9662<\/span><\/p>\n

GDSIG\u8ba1\u7b97\u673a\u89c6\u89c9\u4e13\u59d4\u4f1a<\/span><\/p>\n

<\/span><\/p>\n

\u534f\u529e\uff1a<\/span><\/strong><\/span><\/p>\n

CSIG-\u6587\u6863\u56fe\u50cf\u5206\u6790\u4e0e\u8bc6\u522b\u4e13\u59d4\u4f1a<\/span><\/p>\n

CSIG-\u673a\u5668\u89c6\u89c9\u4e13\u59d4\u4f1a<\/span><\/p>\n

CSIG\u5e7f\u5dde\u4f1a\u5458\u6d3b\u52a8\u4e2d\u5fc3<\/span><\/p>\n

\u65f6\u95f4<\/span><\/strong>\uff1a<\/span><\/strong><\/span><\/strong><\/span><\/p>\n

2024\u5e744\u670827\u65e5\uff08\u661f\u671f\u516d\uff098\uff1a50-17\uff1a20<\/span><\/p>\n

2024\u5e744\u670828\u65e5\uff08\u661f\u671f\u65e5\uff099\uff1a00-12\uff1a10<\/span><\/p>\n

\u76f4\u64ad\u5e73\u53f0\uff1a<\/span><\/strong><\/span><\/p>\n

GDSIG\u89c6\u9891\u53f7<\/span><\/p>\n

\"\u5fae\u4fe1\u56fe\u7247_20240425002722.png\"<\/p>\n

<\/p>\n

B\u7ad9\u5e73\u53f0\uff1a<\/span>https:\/\/live.bilibili.com\/27738963<\/span><\/a><\/p>\n

\u853b\u4eab\u5b66\u672f\uff1a<\/span>https:\/\/www.koushare.com\/live\/details\/33662<\/span><\/a>\u00a0<\/span><\/strong><\/span><\/p>\n

<\/span><\/p>\n

<\/span><\/p>\n

\"image.png\"\/\u00a0<\/span><\/span><\/p>\n

\u56fd\u9645\u8ba1\u7b97\u673a\u89c6\u89c9\u4e0e\u6a21\u5f0f\u8bc6\u522b\u4f1a\u8bae\uff08IEEE International Conference on Computer Vision and Pattern Recognition, CVPR\uff09\u4f5c\u4e3aIEEE\u5e74\u5ea6\u65d7\u8230\u76db\u4f1a\uff0c\u4e0d\u4ec5\u662f\u5168\u7403\u6700\u9876\u5c16\u7684\u8ba1\u7b97\u673a\u89c6\u89c9\u5b66\u672f\u5e73\u53f0\u4e4b\u4e00\uff0c\u66f4\u662f\u5168\u7403\u79d1\u6280\u754c\u9ad8\u5ea6\u5173\u6ce8\u7684\u521b\u65b0\u9ad8\u5730\u3002\u5728\u4e0d\u65ad\u63a8\u9648\u51fa\u65b0\u7684\u79d1\u7814\u6d6a\u6f6e\u4e2d\uff0cCVPR\u4e0a\u53d1\u8868\u7684\u7814\u7a76\u6210\u679c\u4e0d\u4ec5\u6df1\u523b\u5f71\u54cd\u7740\u76f8\u5173\u9886\u57df\u7684\u77e5\u8bc6\u4f53\u7cfb\u6784\u5efa\uff0c\u66f4\u4e3a\u5168\u7403\u79d1\u7814\u4eba\u5458\u63d0\u4f9b\u4e86\u6781\u5177\u4ef7\u503c\u7684\u521b\u65b0\u542f\u793a\u4e0e\u5b9e\u8df5\u6307\u5bfc\u3002<\/span><\/p>\n

\u6839\u636e\u6700\u65b0\u7684Google\u5b66\u672f\u6307\u6807\uff08Google Scholar Metrics\uff09\uff0cCVPR\u5728\u5168\u7403\u5b66\u672f\u51fa\u7248\u7269\u4e2d\u4f4d\u5217\u7b2c4\uff0c\u7d27\u968fNature\u3001The New England Journal of Medicine\u3001Science\u4e4b\u540e\u3002\u5728\u4e2d\u56fd\u8ba1\u7b97\u673a\u5b66\u4f1a\u63a8\u8350\u7684\u56fd\u9645\u5b66\u672f\u4f1a\u8bae\u4f53\u7cfb\u4e2d\uff0cCVPR\u7a33\u5c45\u4eba\u5de5\u667a\u80fd\u9886\u57dfA\u7c7b\u4e4b\u5217\u3002<\/span><\/p>\n

\u503c\u6b64CVPR 2024\u76db\u4f1a\u5373\u5c06\u542f\u5e55\u4e4b\u9645\uff0c\u6211\u4eec\u7279\u522b\u7b56\u5212\u4e86\u4e00\u573a\u7ebf\u4e0a\u5206\u4eab\u4f1a\uff0c\u8bda\u9080\u6765\u81ea\u5e7f\u4e1c\u7701\u5185\u5404\u4f18\u79c0\u7814\u7a76\u56e2\u961f\u768429\u4f4d\u9752\u5e74\u624d\u4fca\uff0c\u4ecb\u7ecd\u4ed6\u4eec\u4eca\u5e74\u88abCVPR 2024\u5f55\u7528\u8bba\u6587\u7684\u7814\u7a76\u6210\u679c\u3002<\/span><\/p>\n

<\/span><\/p>\n

\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0\u00a0 \u00a0 \u00a0 \u4f1a\u8bae\u65e5\u7a0b\u4e00\u89c8\u8868<\/span><\/span><\/strong><\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
\n

2024<\/span>\u5e74<\/span>4<\/span>\u6708<\/span>27<\/span>\u65e5\u4e0a\u5348<\/span> \uff08\u4f1a\u8bae\u4e3b\u6301\u4eba\uff1a\u4e01\u957f\u5174\u3001\u9648\u660c\u76db\uff09<\/span><\/span><\/p>\n<\/td>\n<\/tr>\n

\n

\u65f6\u95f4<\/span><\/strong><\/p>\n<\/td>\n

\n

\u62a5\u544a\u9898\u76ee<\/span><\/strong><\/p>\n<\/td>\n

\n

\u8bba\u6587\u7b2c\u4e00\u4f5c\u8005\uff0c\u5bfc\u5e08<\/span>\/\u901a\u4fe1\u4f5c\u8005<\/span><\/span><\/strong><\/p>\n<\/td>\n<\/tr>\n

\n

8:5<\/span>0-9<\/span>:0<\/span>0<\/span><\/p>\n<\/td>\n

\n

\u4f1a\u8bae\u5f00\u5e55\u81f4\u8f9e<\/span><\/p>\n<\/td>\n

\n

\u8d56\u5251\u714c\u6559\u6388<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

\u8bba\u6587\u4e3b\u9898\uff1a\u8bc6\u522b\u4e0e\u5206\u5272<\/span> <\/span><\/strong>(10 <\/span><\/strong>\u7bc7<\/span><\/strong>)<\/span><\/strong><\/p>\n<\/td>\n<\/tr>\n

\n

9<\/span>:<\/span>00<\/span>–<\/span>9<\/span>:<\/span>20<\/span><\/p>\n<\/td>\n

\n

View-decoupled Transformer for Person Re-identification under Aerial-ground Camera Network<\/span><\/p>\n

\u57fa\u4e8e\u89c6\u89d2\u89e3\u8026\u81ea\u6ce8\u610f\u529b\u6a21\u578b\u7684\u7a7a\u5730\u884c\u4eba\u91cd\u8bc6\u522b\u65b9\u6cd5<\/span><\/p>\n<\/td>\n

\n

\u5f20\u6743\uff0c\u8d56\u5251\u714c<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

9<\/span>:<\/span>20\u20139<\/span>:4<\/span>0<\/span><\/p>\n<\/td>\n

\n

Multi-scale Dynamic and Hierarchical Relationship Modeling for Facial Action Units Recognition<\/span><\/p>\n

\u57fa\u4e8e\u591a\u5c3a\u5ea6\u52a8\u6001\u548c\u5c42\u6b21\u5173\u7cfb\u5efa\u6a21\u7684\u9762\u90e8\u52a8\u4f5c\u5355\u5143\u8bc6\u522b<\/span><\/p>\n<\/td>\n

\n

\u6c6a\u5b50\u6657\uff0c\u6c88\u7433\u7433<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

9<\/span>:4<\/span>0-10<\/span>:0<\/span>0<\/span><\/p>\n<\/td>\n

\n

BigGait: Learning Gait Representation You Want by Large Vision Models<\/span><\/p>\n

\u5927\u6b65\u6001<\/span>: \u4ece\u89c6\u89c9\u5927\u6a21\u578b\u4e2d\u5b66\u5230\u4f60\u60f3\u8981\u7684\u6b65\u6001\u7279\u5f81<\/span><\/span><\/p>\n<\/td>\n

\n

Dingqiang Ye<\/span>\uff0c<\/span><\/p>\n

\u4e8e\u4ed5\u742a<\/span>\/\u5218\u6653\u660e<\/span><\/span><\/p>\n<\/td>\n<\/tr>\n

\n

10<\/span>:0<\/span>0-10<\/span>:2<\/span>0<\/span><\/p>\n<\/td>\n

\n

AlignSAM: Aligning Segment Anything Model to Open Context via Reinforcement Learning<\/span><\/p>\n

\u5229\u7528\u5f3a\u5316\u5b66\u4e60\u5c06\u5206\u5272\u4e00\u5207\u6a21\u578b\u5bf9\u9f50\u5230\u5f00\u653e\u8bed\u5883<\/span><\/p>\n<\/td>\n

\n

\u9ec4\u94ce\u5cfb\uff0c\u674e\u51a0\u5f6c<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

10<\/span>:<\/span>20-10<\/span>:<\/span>40<\/span><\/p>\n<\/td>\n

\n

Bridging the Gap Between End-to-End and Two-Step Text Spotting<\/span><\/p>\n

\u7f29\u5c0f\u7aef\u5230\u7aef\u6587\u672c\u8bc6\u522b\u548c\u4e24\u9636\u6bb5\u6587\u672c\u8bc6\u522b\u7684\u5dee\u8ddd<\/span><\/p>\n<\/td>\n

\n

\u9ec4\u660e\u946b\uff0c\u91d1\u8fde\u6587<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

10<\/span>:<\/span>40-11<\/span>:0<\/span>0<\/span><\/p>\n<\/td>\n

\n

APSeg: Auto-Prompt Network for Cross-Domain Few-Shot Semantic Segmentation<\/span><\/p>\n

APSeg: \u7528\u4e8e\u8de8\u57df\u5c0f\u6837\u672c\u8bed\u4e49\u5206\u5272\u7684\u81ea\u52a8\u63d0\u793a\u7f51\u7edc<\/span><\/span><\/p>\n<\/td>\n

\n

\u4f55\u4f1f\u948a\uff0c<\/span><\/p>\n

\u5f20\u6d0b<\/span>\/\u5353\u709c<\/span><\/span><\/p>\n<\/td>\n<\/tr>\n

\n

11:0<\/span>0-<\/span>11:2<\/span>0<\/span><\/p>\n<\/td>\n

\n

DiffForensics: Leveraging Diffusion Prior to Image Forgery Detection and Localization<\/span><\/p>\n

DiffForensics: \u5c06\u6269\u6563\u5148\u9a8c\u7528\u4e8e\u56fe\u50cf\u7be1\u6539\u68c0\u6d4b\u4e0e\u5b9a\u4f4d<\/span><\/span><\/p>\n<\/td>\n

\n

\u4f59\u6cfd\u94a6\uff0c<\/span><\/p>\n

\u502a\u6c5f\u7fa4<\/span>\/\u674e\u658c<\/span><\/span><\/p>\n<\/td>\n<\/tr>\n

\n

1<\/span>1<\/span>:2<\/span>0-11<\/span>:4<\/span>0<\/span><\/p>\n<\/td>\n

\n

CMA: A Chromaticity Map Adapter for Robust Detection of Screen-Recapture Document Images<\/span><\/p>\n

CMA\uff1a\u7528\u4e8e\u9c81\u68d2\u68c0\u6d4b\u5c4f\u5e55\u7ffb\u62cd\u6587\u6863\u56fe\u50cf\u7684\u8272\u5ea6\u7279\u5f81\u56fe\u9002\u914d\u5668<\/span><\/span><\/p>\n<\/td>\n

\n

\u6797\u826f\u5a01\uff0c\u9648\u660c\u76db<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

1<\/span>1<\/span>:<\/span>40-12<\/span>:<\/span>00<\/span><\/p>\n<\/td>\n

\n

Towards Modern Image Manipulation Localization: A Large-Scale Dataset and Novel Methods<\/span><\/p>\n

\u9762\u5411\u73b0\u4ee3\u98ce\u683c\u56fe\u50cf\u7684\u7be1\u6539\u5b9a\u4f4d\uff1a\u4e00\u4e2a\u5927\u89c4\u6a21\u6570\u636e\u96c6\u548c\u65b0\u9896\u7684\u65b9\u6cd5<\/span><\/p>\n<\/td>\n

\n

\u66f2\u6668\u5e06\uff0c<\/span><\/p>\n

\u91d1\u8fde\u6587<\/span>\/\u949f\u4ea6\u6b66<\/span><\/span><\/p>\n<\/td>\n<\/tr>\n

\n

12:0<\/span>0-12<\/span>:2<\/span>0<\/span><\/p>\n<\/td>\n

\n

S<\/span><\/span>Learning Background Prompts to Discover Implicit Knowledge for Open Vocabulary Object Detection<\/span><\/p>\n

\u901a\u8fc7\u5b66\u4e60\u80cc\u666f\u63d0\u793a\u53d1\u73b0\u5f00\u653e\u8bcd\u6c47\u76ee\u6807\u68c0\u6d4b\u4e2d\u7684\u9690\u542b\u77e5\u8bc6<\/span><\/p>\n<\/td>\n

\n

\u674e\u4f73\u94ed\uff0c\u674e\u51a0\u5f6c<\/span><\/p>\n

\u00a0<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

2024\u5e744\u670827\u65e5\u4e0b\u5348\uff08\u4f1a\u8bae\u4e3b\u6301\u4eba\uff1a<\/span>\u8c22\u6653\u534e\u3001\u5f20\u946b<\/span>\uff09<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

\u65f6\u95f4<\/span><\/strong><\/p>\n<\/td>\n

\n

\u8bba\u6587\u9898\u76ee<\/span><\/span><\/strong><\/p>\n<\/td>\n

\n

\u8bba\u6587\u7b2c\u4e00\u4f5c\u8005\uff0c\u5bfc\u5e08<\/span>\/\u901a\u4fe1\u4f5c\u8005<\/span><\/span><\/strong><\/p>\n<\/td>\n<\/tr>\n

\n

\u8bba\u6587\u4e3b\u9898\uff1a\u5185\u5bb9\u751f\u6210<\/span> <\/span><\/strong>(10 <\/span><\/strong>\u7bc7<\/span><\/strong>)<\/span><\/strong><\/p>\n<\/td>\n<\/tr>\n

\n

14<\/span>:0<\/span>0-14<\/span>:2<\/span>0<\/span><\/p>\n<\/td>\n

\n

Single-View Scene Point Cloud Human Grasp Generation<\/span><\/p>\n

\u5355\u89c6\u89d2\u573a\u666f\u70b9\u4e91\u4eba\u624b\u6293\u53d6\u751f\u6210<\/span><\/p>\n<\/td>\n

\n

\u738b\u708e\u5eb7\uff0c\u90d1\u4f1f\u8bd7<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

14<\/span>:2<\/span>0-14<\/span>:4<\/span>0<\/span><\/p>\n<\/td>\n

\n

Coarse-to-Fine Latent Diffusion for Pose-Guided Person Image Synthesis<\/span><\/p>\n

\u7531\u7c97\u5230\u7ec6\u7684\u6f5c\u5728\u6269\u6563\u7528\u4e8e\u59ff\u52bf\u5f15\u5bfc\u4eba\u7269\u56fe\u50cf\u5408\u6210<\/span><\/p>\n<\/td>\n

\n

\u5362\u5f66\u4f5c\uff0c<\/span><\/p>\n

\u9a6c\u9526\u534e<\/span>\/\u8c22\u6653\u534e<\/span><\/span><\/p>\n<\/td>\n<\/tr>\n

\n

14<\/span>:4<\/span>0-15<\/span>:0<\/span>0<\/span><\/p>\n<\/td>\n

\n

Texture-Preserving Diffusion Models for High-Fidelity Virtual Try-On<\/span><\/p>\n

\u7528\u4e8e\u9ad8\u4fdd\u771f\u865a\u62df\u8bd5\u7a7f\u7684\u4fdd\u6301\u7eb9\u7406\u7684\u6269\u6563\u6a21\u578b<\/span><\/p>\n<\/td>\n

\n

\u6768\u7166\uff0c\u4e01\u957f\u5174<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

15<\/span>:0<\/span>0-15<\/span>:2<\/span>0<\/span><\/p>\n<\/td>\n

\n

360DVD: Controllable Panorama Video Generation with 360-Degree Video Diffusion Model<\/span><\/p>\n

360DVD\uff1a\u57fa\u4e8e<\/span>360<\/span>\u5ea6\u89c6\u9891\u6269\u6563\u6a21\u578b\u7684\u5168\u666f\u89c6\u9891\u751f\u6210<\/span><\/span><\/p>\n<\/td>\n

\n

\u738b\u831c\uff0c\u5f20\u5065<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

15<\/span>:2<\/span>0-15<\/span>:4<\/span>0<\/span><\/p>\n<\/td>\n

\n

Text-conditional Attribute Alignment across Latent Spaces for 3D Controllable Face Image Synthesis<\/span><\/p>\n

\u57fa\u4e8e\u6f5c\u7a7a\u95f4\u4e0b\u6587\u672c\u5b9a\u4e49\u5c5e\u6027\u5bf9\u9f50\u7684\u4e09\u7ef4\u53ef\u63a7\u4eba\u8138\u56fe\u50cf\u751f\u6210<\/span><\/p>\n<\/td>\n

\n

\u5f90\u975e\u51e1\uff0c<\/span><\/p>\n

\u5434\u65af<\/span>\/<\/span><\/span>\u674e\u745e<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

15<\/span>:4<\/span>0-16<\/span>:<\/span>00<\/span><\/p>\n<\/td>\n

\n

Towards Variable and Coordinated Holistic Co-Speech Motion Generation<\/span><\/p>\n

\u9762\u5411\u53ef\u53d8\u4e14\u534f\u8c03\u7684\u5168\u8eab\u8bed\u97f3\u52a8\u4f5c\u751f\u6210<\/span><\/p>\n<\/td>\n

\n

\u5218\u7ffc\u98de\uff0c<\/span><\/p>\n

\u4e01\u957f\u5174<\/span>\/\u66f9\u743c<\/span><\/span><\/p>\n<\/td>\n<\/tr>\n

\n

16<\/span>:0<\/span>0-16<\/span>:2<\/span>0<\/span><\/p>\n<\/td>\n

\n

Tackling the Singularities at the Endpoints of Time Intervals in Diffusion Models<\/span><\/p>\n

\u89e3\u51b3\u6269\u6563\u6a21\u578b\u4e2d\u65f6\u95f4\u95f4\u9694\u7aef\u70b9\u7684\u5947\u5f02\u6027<\/span><\/p>\n<\/td>\n

\n

\u5f20\u9e4f\u6cfd\uff0c\u8c22\u6653\u534e<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

16<\/span>:2<\/span>0-16<\/span>:4<\/span>0<\/span><\/p>\n<\/td>\n

\n

NeRF-HuGS: Improved Neural Radiance Fields in Non-static Scenes Using Heuristics-Guided Segmentation<\/span><\/p>\n

NeRF-HuGS: \u5728\u975e\u9759\u6001\u573a\u666f\u4e2d\u4f7f\u7528\u542f\u53d1\u5f0f\u5f15\u5bfc\u5206\u5272\u6539\u8fdb\u7684\u795e\u7ecf\u8f90\u5c04\u573a<\/span><\/span><\/p>\n<\/td>\n

\n

\u9648\u5bb6\u8c6a\uff0c\u674e\u51a0\u5f6c<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

16<\/span>:4<\/span>0-17<\/span>:0<\/span>0<\/span><\/p>\n<\/td>\n

\n

AlignMiF: Geometry-Aligned Multimodal Implicit Field for LiDAR-Camera Joint Synthesis<\/span><\/p>\n

AlignMiF\uff1a\u7528\u4e8e\u96f7\u8fbe<\/span>–<\/span>\u76f8\u673a\u8054\u5408\u5408\u6210\u7684\u51e0\u4f55\u5bf9\u9f50\u591a\u6a21\u6001\u9690\u5f0f\u573a<\/span><\/span><\/p>\n<\/td>\n

\n

\u5510\u6d9b\uff0c<\/span><\/p>\n

\u6881\u5c0f\u4e39<\/span>\/\u4e8e\u5f00\u4e1e<\/span><\/span><\/p>\n<\/td>\n<\/tr>\n

\n

1<\/span>7:0<\/span>0-1<\/span>7:2<\/span>0<\/span><\/p>\n<\/td>\n

\n

Neural Customizable Human Avatar<\/span><\/p>\n

\u53ef\u5b9a\u5236\u5316\u6570\u5b57\u4eba<\/span><\/p>\n<\/td>\n

\n

\u8096\u4fca\u9526\uff0c\u5f20\u9752<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

2024\u5e744\u670828\u65e5<\/span>\u4e0a<\/span>\u5348\uff08\u4f1a\u8bae\u4e3b\u6301\u4eba\uff1a<\/span>\u4e8e\u4ed5\u742a\u3001\u5f20\u9752<\/span>\uff09<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

\u65f6\u95f4<\/span><\/strong><\/p>\n<\/td>\n

\n

\u8bba\u6587\u9898\u76ee<\/span><\/strong><\/p>\n<\/td>\n

\n

\u8bba\u6587\u7b2c\u4e00\u4f5c\u8005\uff0c\u5bfc\u5e08<\/span>\/\u901a\u4fe1\u4f5c\u8005<\/span><\/span><\/strong><\/p>\n<\/td>\n<\/tr>\n

\n

\u8bba\u6587\u4e3b\u9898\uff1a\u56fe\u50cf\u6062\u590d\u4e0e\u8868\u5f81\u5b66\u4e60<\/span> <\/span><\/strong>(9<\/span><\/strong>\u7bc7<\/span><\/strong>)<\/span><\/strong><\/p>\n<\/td>\n<\/tr>\n

\n

9<\/span>:0<\/span>0-<\/span>9<\/span>:2<\/span>0<\/span><\/p>\n<\/td>\n

\n

VRetouchEr: Learning Cross-frame Feature Interdependence with Imperfection Flow for Face Retouching in Videos<\/span><\/p>\n

VRetouchEr:\u5b66\u4e60\u8de8\u5e27\u529f\u80fd\u76f8\u4e92\u4f9d\u5b58\u4e0e\u4e0d\u5b8c\u7f8e\u6d41\u5728\u89c6\u9891\u4e2d\u7684\u9762\u90e8\u4fee\u9970<\/span><\/span><\/p>\n<\/td>\n

\n

\u859b\u6587\uff0c<\/span><\/p>\n

\u5434\u65af<\/span>\/\u8bb8\u52c7<\/span><\/span><\/p>\n<\/td>\n<\/tr>\n

\n

9<\/span>:<\/span>20\u20139<\/span>:4<\/span>0<\/span><\/p>\n<\/td>\n

\n

CoSeR: Bridging Image and Language for Cognitive Super-Resolution<\/span><\/p>\n

CoSeR\uff1a\u8fde\u63a5\u56fe\u50cf\u4e0e\u8bed\u8a00\uff0c\u5b9e\u73b0\u8ba4\u77e5\u8d85\u5206\u8fa8\u7387<\/span><\/span><\/p>\n<\/td>\n

\n

Haoze Sun<\/span>\uff0c<\/span>Yujiu Yang<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

9<\/span>:4<\/span>0-10<\/span>:0<\/span>0<\/span><\/p>\n<\/td>\n

\n

Learning to Remove Wrinkled Transparent Film with Polarized Prior<\/span><\/p>\n

\u901a\u8fc7\u504f\u632f\u5148\u9a8c\u53bb\u9664\u8936\u76b1\u900f\u660e\u8584\u819c<\/span><\/p>\n<\/td>\n

\n

Jiaqi Tang<\/span>\uff0c<\/span>Ying-Cong Chen<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

10<\/span>:0<\/span>0-10<\/span>:2<\/span>0<\/span><\/p>\n<\/td>\n

\n

Learning Degradation-unaware Representation with Prior-based Latent Transformations for Blind Face Restoration<\/span><\/p>\n

\u57fa\u4e8e\u5148\u9a8c\u7684\u6f5c\u53d8\u6362\u5b66\u4e60\u5bf9\u9000\u5316\u4e0d\u654f\u611f\u7684\u8868\u5f81\u4ee5\u5b9e\u73b0\u76f2\u8138\u6062\u590d<\/span><\/p>\n<\/td>\n

\n

\u8c22\u70bc\u65b0\uff0c\u5434\u65af<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

10<\/span>:<\/span>20-10<\/span>:<\/span>40<\/span><\/p>\n<\/td>\n

\n

Incremental Residual Concept Bottleneck Models<\/span><\/p>\n

\u589e\u91cf\u5f0f\u6b8b\u5dee\u6982\u5ff5\u74f6\u9888\u6a21\u578b<\/span><\/p>\n<\/td>\n

\n

\u5c1a\u8fb0\u94ed\uff0c<\/span><\/p>\n

\u6768\u4f59\u4e45<\/span>\/\u738b\u7389\u65fa<\/span><\/span><\/p>\n<\/td>\n<\/tr>\n

\n

10<\/span>:<\/span>40-11<\/span>:0<\/span>0<\/span><\/p>\n<\/td>\n

\n

EditGuard: Versatile Image Watermarking for Tamper Localization and Copyright Protection<\/span><\/p>\n

EditGuard\uff1a\u8054\u5408\u7be1\u6539\u5b9a\u4f4d\u548c\u7248\u6743\u4fdd\u62a4\u7684\u591a\u529f\u80fd\u56fe\u50cf\u6c34\u5370<\/span><\/span><\/p>\n<\/td>\n

\n

\u5f20\u8f69\u5b87\uff0c\u5f20\u5065<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

11:0<\/span>0-<\/span>11:2<\/span>0<\/span><\/p>\n<\/td>\n

\n

Deep Unsupervised Unrolling Networks for Phase Unwrapping<\/span><\/p>\n

\u9488\u5bf9\u76f8\u4f4d\u5c55\u5f00\u7684\u6df1\u5ea6\u65e0\u76d1\u7763\u5c55\u5f00\u7f51\u7edc\u7814\u7a76<\/span><\/p>\n<\/td>\n

\n

\u9648\u5fd7\u4e50\uff0c\u5168\u5b87\u6656<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

1<\/span>1<\/span>:2<\/span>0-11<\/span>:4<\/span>0<\/span><\/p>\n<\/td>\n

\n

Latent Modulated Function for Computational Optimal Continuous Image Representation<\/span><\/p>\n

\u57fa\u4e8e\u9690\u8c03\u5236\u51fd\u6570\u7684\u8ba1\u7b97\u6700\u4f18\u8fde\u7eed\u56fe\u50cf\u8868\u793a<\/span><\/p>\n<\/td>\n

\n

\u4f55\u5b97\u8000\uff0c\u91d1\u679d<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

1<\/span>1<\/span>:<\/span>40-12<\/span>:<\/span>00<\/span><\/p>\n<\/td>\n

\n

Learning Adaptive Spatial Coherent Correlations for Speech-Preserving Facial Expression Manipulation<\/span><\/p>\n

\u4e3a\u4fdd\u7559\u8bed\u97f3\u7684\u9762\u90e8\u8868\u60c5\u64cd\u4f5c\u5b66\u4e60\u81ea\u9002\u5e94\u7a7a\u95f4\u4e00\u81f4\u6027\u5173\u8054<\/span><\/p>\n<\/td>\n

\n

\u6797\u575a\u6ee1\uff0c\u9648\u6dfb\u6c34<\/span><\/p>\n<\/td>\n<\/tr>\n

\n

12<\/span>:<\/span>00-12<\/span>:<\/span>10<\/span><\/p>\n<\/td>\n

\n

\u95ed\u5e55\u5f0f\u81f4\u8f9e<\/span> \uff08\u91d1\u8fde\u6587\u6559\u6388\uff09<\/span><\/span><\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

<\/p>\n

\u62a5\u540d<\/span><\/strong>\u6ce8\u518c<\/span><\/strong><\/span><\/p>\n

1.\u00a0\u672c\u6b21\u5728\u7ebf\u4f1a\u8bae\u514d\u8d39\u53c2\u52a0\uff0c\u4e0d\u6536\u53d6\u4efb\u4f55\u6ce8\u518c\u8d39\uff0c\u4e0d\u7528\u63d0\u524d\u62a5\u540d\u6ce8\u518c\u3002<\/span><\/p>\n

2.\u00a0\u666e\u901a\u542c\u4f17\u8bf7\u901a\u8fc7\u76f4\u64ad\u7f51\u5740\u53c2\u52a0\u4f1a\u8bae\u3002<\/span><\/p>\n

3.\u00a0<\/span>\u7279\u9080\u8bb2\u8005\u53ca\u5609\u5bbe\u3001GDSIG\u7406\u4e8b\uff0c\u4f1a\u8baeID\u53e6\u884c\u901a\u77e5\u3002<\/span><\/p>\n

<\/span><\/p>\n

\u7ec4\u59d4\u4f1a<\/span><\/strong><\/span><\/p>\n

\u91d1\u8fde\u6587\uff0c\u534e\u5357\u7406\u5de5\u5927\u5b66\u7535\u5b50\u4e0e\u4fe1\u606f\u5b66\u9662<\/span><\/p>\n

\u90d1\u4f1f\u8bd7\uff0c\u4e2d\u5c71\u5927\u5b66\u8ba1\u7b97\u673a\u5b66\u9662<\/span><\/p>\n

\u5f20\u00a0\u946b\uff0c\u534e\u5357\u7406\u5de5\u5927\u5b66\u7535\u5b50\u4e0e\u4fe1\u606f\u5b66\u9662<\/span><\/p>\n

\u8c22\u6653\u534e\uff0c\u4e2d\u5c71\u5927\u5b66\u8ba1\u7b97\u673a\u5b66\u9662<\/span><\/p>\n

\u5f20\u00a0\u9752\uff0c\u4e2d\u5c71\u5927\u5b66\u8ba1\u7b97\u673a\u5b66\u9662<\/span><\/p>\n

\u4e8e\u4ed5\u742a\uff0c\u5357\u65b9\u79d1\u6280\u5927\u5b66\u8ba1\u7b97\u673a\u79d1\u5b66\u4e0e\u5de5\u7a0b\u7cfb<\/span><\/p>\n

\u9648\u660c\u76db\uff0c\u6df1\u5733\u5927\u5b66\u7535\u5b50\u4e0e\u4fe1\u606f\u5de5\u7a0b\u5b66\u9662<\/span><\/p>\n

<\/span><\/p>\n

\u8054\u7cfb\u4eba<\/span><\/strong><\/span><\/p>\n

\u5f20\u8001\u5e08\uff0cEmail:\u00a0<\/span>eexinzhang@scut.edu.cn<\/a>\u00a0<\/span><\/p>\n

\u8c22\u8001\u5e08\uff0cEmail:\u00a0<\/span>xiexiaoh6@mail.sysu.edu.cn<\/a>\u00a0<\/span><\/p>\n

<\/p>\n

\"\u56fe\u72473.png\"<\/p>\n

<\/p>\n


<\/p>\n


<\/p>\n

<\/p>\n","protected":false},"excerpt":{"rendered":"

\u4e3b\u529e\uff1a\u5e7f\u4e1c\u7701\u56fe\u8c61\u56fe\u5f62\u5b66\u4f1a\uff08GDSIG\uff09\u627f\u529e\uff1a\u534e\u5357\u7406\u5de5\u5927\u5b66\u7535\u5b50\u4e0e\u4fe1\u606f\u5b66\u9662\u4e2d\u5c71\u5927\u5b66\u8ba1\u7b97\u673a\u5b66\u9662\u6df1\u5733\u5927\u5b66\u7535\u5b50\u4e0e\u4fe1\u606f\u5de5\u7a0b\u5b66\u9662\u5357\u65b9\u79d1\u6280\u5927\u5b66\u8ba1\u7b97\u673a\u79d1\u5b66\u4e0e\u5de5\u7a0b\u5b66\u9662GDSIG\u8ba1\u7b97\u673a\u89c6\u89c9\u4e13\u59d4\u4f1a\u534f\u529e\uff1aCSIG-\u6587\u6863\u56fe\u50cf\u5206\u6790\u4e0e\u8bc6\u522b\u4e13\u59d4\u4f1aCSIG-\u673a\u5668\u89c6\u89c9\u4e13\u59d4\u4f1aCSIG\u5e7f\u5dde\u4f1a\u5458\u6d3b\u52a8\u4e2d\u5fc3\u65f6\u95f4\uff1a2024\u5e744\u67082<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[5],"tags":[],"class_list":["post-1171","post","type-post","status-publish","format-standard","hentry","category-s12"],"_links":{"self":[{"href":"https:\/\/test.gdsig.cn\/index.php\/wp-json\/wp\/v2\/posts\/1171","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/test.gdsig.cn\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/test.gdsig.cn\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/test.gdsig.cn\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/test.gdsig.cn\/index.php\/wp-json\/wp\/v2\/comments?post=1171"}],"version-history":[{"count":0,"href":"https:\/\/test.gdsig.cn\/index.php\/wp-json\/wp\/v2\/posts\/1171\/revisions"}],"wp:attachment":[{"href":"https:\/\/test.gdsig.cn\/index.php\/wp-json\/wp\/v2\/media?parent=1171"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/test.gdsig.cn\/index.php\/wp-json\/wp\/v2\/categories?post=1171"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/test.gdsig.cn\/index.php\/wp-json\/wp\/v2\/tags?post=1171"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}