{"id":24761,"date":"2025-03-03T09:49:23","date_gmt":"2025-03-03T01:49:23","guid":{"rendered":"https:\/\/aif.amtbbs.org\/?p=24761"},"modified":"2025-03-03T09:49:23","modified_gmt":"2025-03-03T01:49:23","slug":"iclr-2025%ef%bd%9cai%e4%b8%8d%e8%af%ad%ef%bc%8c%e5%8f%aa%e6%98%af%e4%b8%80%e5%91%b3%e6%a0%b9%e6%8d%ae%e4%ba%ba%e7%b1%bb%e6%84%8f%e5%9b%be%e6%8e%a8%e7%90%863d%e7%a9%ba%e9%97%b4%e5%ae%9a%e4%bd%8d","status":"publish","type":"post","link":"https:\/\/aif.amtbbs.org\/index.php\/2025\/03\/03\/24761\/","title":{"rendered":"ICLR 2025\uff5cAI\u4e0d\u8bed\uff0c\u53ea\u662f\u4e00\u5473\u6839\u636e\u4eba\u7c7b\u610f\u56fe\u63a8\u74063D\u7a7a\u95f4\u5b9a\u4f4d"},"content":{"rendered":"
\"\"<\/div>\n
\u5728\u73b0\u5b9e\u4e16\u754c\u4e2d\uff0cAI \u80fd\u591f\u6839\u636e\u81ea\u7136\u8bed\u8a00\u6307\u4ee4\u6267\u884c\u76ee\u6807\u68c0\u6d4b\uff0c\u5bf9\u4eba\u673a\u4ea4\u4e92\u81f3\u5173\u91cd\u8981\u3002\u8fc7\u53bb\u7684\u7814\u7a76\u4e3b\u8981\u96c6\u4e2d\u5728\u89c6\u89c9\u6307\u5f15\uff08Visual Grounding\uff09\u3002<\/div>\n
\n
\n

\"\"<\/p>\n

\u56fe\u4e00\uff1a\u6211\u4eec\u5f15\u5165\u4e86 3D \u610f\u56fe\u5b9a\u4f4d\uff08\u53f3\uff09\uff0c\u8fd9\u4e00\u65b0\u4efb\u52a1\u65e8\u5728\u6839\u636e\u4eba\u7c7b\u610f\u56fe\u53e5\u5b50\uff08\u4f8b\u5982\uff1a\u201c\u6211\u60f3\u8981\u4e00\u4e2a\u80fd\u652f\u6491\u6211\u7684\u80cc\u90e8\u3001\u7f13\u89e3\u538b\u529b\u7684\u7269\u54c1\u201d\uff09\uff0c\u5728 3D \u573a\u666f\u4e2d\u901a\u8fc7 3D \u8fb9\u754c\u6846\u68c0\u6d4b\u76ee\u6807\u7269\u4f53\u3002\u76f8\u6bd4\u4e4b\u4e0b\uff0c\u73b0\u6709\u7684 3D \u89c6\u89c9\u5b9a\u4f4d\uff08\u5de6\uff09\u4f9d\u8d56\u4e8e\u4eba\u7c7b\u7684\u63a8\u7406\u548c\u53c2\u8003\u6765\u8fdb\u884c\u68c0\u6d4b\u3002\u8be5\u793a\u610f\u56fe\u6e05\u6670\u5730\u533a\u5206\u4e86\u89c2\u5bdf\u548c\u63a8\u7406\u7684\u6267\u884c\u65b9\u5f0f\uff1a\u5de6\u4fa7\u7531\u4eba\u7c7b\u624b\u52a8\u5b8c\u6210\uff0c\u53f3\u4fa7\u5219\u7531 AI \u81ea\u52a8\u5b8c\u6210\u3002<\/p>\n

\"\"<\/p>\n

    \n
  • \u9879\u76ee\u4e3b\u9875\uff1ahttps:\/\/weitaikang.github.io\/Intent3D-webpage\/<\/li>\n
  • \u8bba\u6587\u5730\u5740\uff1ahttps:\/\/arxiv.org\/abs\/2405.18295<\/li>\n
  • \u9879\u76ee\u4ee3\u7801\uff1ahttps:\/\/github.com\/WeitaiKang\/Intent3D<\/li>\n<\/ul>\n

    \u4ecb\u7ecd<\/h4>\n

    \u5728\u73b0\u5b9e\u4e16\u754c\u4e2d\uff0cAI \u80fd\u591f\u6839\u636e\u81ea\u7136\u8bed\u8a00\u6307\u4ee4\u6267\u884c\u76ee\u6807\u68c0\u6d4b\uff0c\u5bf9\u4eba\u673a\u4ea4\u4e92\u81f3\u5173\u91cd\u8981\u3002\u8fc7\u53bb\u7684\u7814\u7a76\u4e3b\u8981\u96c6\u4e2d\u5728\u89c6\u89c9\u6307\u5f15\uff08Visual Grounding\uff09\uff0c\u5373\u6839\u636e\u4eba\u7c7b\u63d0\u4f9b\u7684\u53c2\u7167\u6027\u8bed\u8a00\uff0c\u5728 2D \u56fe\u50cf\u6216 3D \u573a\u666f\u4e2d\u5b9a\u4f4d\u76ee\u6807\u7269\u4f53\u3002<\/p>\n

    \u7136\u800c\uff0c\u4eba\u7c7b\u5728\u65e5\u5e38\u751f\u6d3b\u4e2d\u5bfb\u627e\u76ee\u6807\u7269\u54c1\u5f80\u5f80\u662f\u8d77\u6e90\u4e8e\u67d0\u4e2a\u7279\u5b9a\u7684\u610f\u56fe\u3002\u4f8b\u5982\uff0c\u4e00\u4e2a\u4eba\u53ef\u80fd\u4f1a\u8bf4\uff1a\u201c\u6211\u60f3\u627e\u4e2a\u4e1c\u897f\u9760\u7740\uff0c\u4ee5\u7f13\u89e3\u80cc\u90e8\u538b\u529b\u201d\uff0c\u800c\u4e0d\u662f\u6beb\u65e0\u7406\u7531\u7684\u76f4\u63a5\u63cf\u8ff0 \u201c\u627e\u5230\u6905\u5b50\u201d \u6216 \u201c\u627e\u5230\u6c99\u53d1\u201d\u3002<\/p>\n

    \u4ec0\u4e48\u662f 3D \u610f\u56fe\u5b9a\u4f4d\uff083D-IG\uff09\uff1f<\/strong><\/p>\n

    \u76ee\u524d\uff0c3D \u89c6\u89c9\u6307\u5f15\uff083D Visual Grounding, 3D-VG\uff09\u65b9\u6cd5\u4f9d\u8d56\u7528\u6237\u63d0\u4f9b\u660e\u786e\u7684\u53c2\u7167\u4fe1\u606f\uff0c\u5982\u76ee\u6807\u7684\u7c7b\u522b\u3001\u5c5e\u6027\u6216\u7a7a\u95f4\u5173\u7cfb\u3002\u4f46\u5728\u8bb8\u591a\u73b0\u5b9e\u573a\u666f\u4e0b\uff0c\u4f8b\u5982\u4eba\u5728\u5fd9\u788c\u6216\u6709\u89c6\u89c9\u969c\u788d\u65f6\uff0c\u65e0\u6cd5\u63d0\u4f9b\u8fd9\u6837\u7684\u53c2\u7167\u63cf\u8ff0\u3002\u56e0\u6b64\uff0c\u8ba9 AI \u80fd\u591f\u81ea\u52a8\u63a8\u7406\u7528\u6237\u7684\u610f\u56fe\u5e76\u68c0\u6d4b\u76ee\u6807\u7269\u4f53\uff0c\u624d\u662f\u66f4\u667a\u80fd\u3001\u66f4\u81ea\u7136\u7684\u4ea4\u4e92\u65b9\u5f0f\u3002\u5982\u56fe\u4e00\u6240\u793a\uff0c\u76f8\u8f83\u4e8e\u4f20\u7edf 3D-VG\uff08\u5de6\u56fe\uff09\uff0c\u6211\u4eec\u7684 3D-IG \u4efb\u52a1\uff08\u53f3\u56fe\uff09\u80fd\u591f\u8ba9 AI \u76f4\u63a5\u57fa\u4e8e\u7528\u6237\u7684\u610f\u56fe\u63a8\u7406\u76ee\u6807\uff0c\u800c\u65e0\u9700\u660e\u786e\u7684\u7269\u4f53\u63cf\u8ff0\u3002<\/p>\n

    \u4e3a\u4ec0\u4e48\u9009\u62e9 3D \u800c\u975e 2D\uff1f<\/strong><\/p>\n

    \u8fd1\u5e74\u6765\uff0c\u57fa\u4e8e\u610f\u56fe\u7684\u63a8\u7406\u4efb\u52a1\u5728 2D \u89c6\u89c9\u9886\u57df\u6709\u6240\u7814\u7a76\uff0c\u5982\u610f\u56fe\u5bfc\u5411\u7684\u76ee\u6807\u68c0\u6d4b\uff08Intention-Oriented Object Detection\uff09\u3001\u9690\u5f0f\u6307\u4ee4\u7406\u89e3\uff08Implicit Instruction Understanding\uff09\u7b49\u3002\u7136\u800c\uff0c\u8fd9\u4e9b\u7814\u7a76\u4ec5\u9650\u4e8e 2D \u89c6\u89d2\uff0c\u65e0\u6cd5\u5b8c\u6574\u53cd\u6620\u73b0\u5b9e\u4e16\u754c\u7684\u51e0\u4f55\u548c\u7a7a\u95f4\u4fe1\u606f\u3002\u76f8\u6bd4\u4e4b\u4e0b\uff0c3D \u6570\u636e\u66f4\u52a0\u8d34\u8fd1\u73b0\u5b9e\u4e16\u754c\uff0c\u4e0d\u4ec5\u5305\u542b\u6df1\u5ea6\u4fe1\u606f\uff0c\u8fd8\u80fd\u63d0\u4f9b\u5b8c\u6574\u7684\u7269\u4f53\u51e0\u4f55\u3001\u5916\u89c2\u7279\u5f81\u4ee5\u53ca\u7a7a\u95f4\u4e0a\u4e0b\u6587\u3002\u56e0\u6b64\uff0c\u5728 3D \u573a\u666f\u4e2d\u8fdb\u884c\u610f\u56fe\u63a8\u7406\uff0c\u4e0d\u4ec5\u80fd\u66f4\u51c6\u786e\u5730\u6a21\u62df\u771f\u5b9e\u9700\u6c42\uff0c\u8fd8\u80fd\u63a8\u52a8\u667a\u80fd\u4f53\uff08Embodied AI\uff09\u3001\u81ea\u52a8\u9a7e\u9a76\u3001AR\/VR \u7b49\u9886\u57df\u7684\u53d1\u5c55\u3002<\/p>\n

    \u6570\u636e\u96c6 & \u57fa\u51c6<\/h4>\n

    \u4e3a\u4e86\u63a8\u52a8 3D \u610f\u56fe\u5b9a\u4f4d\u7814\u7a76\uff0c\u6211\u4eec\u6784\u5efa\u4e86 Intent3D \u6570\u636e\u96c6\uff0c\u5305\u542b 44,990 \u6761\u610f\u56fe\u6587\u672c\uff0c\u6d89\u53ca 209 \u7c7b\u7269\u4f53\uff0c\u57fa\u4e8e 1,042 \u4e2a ScanNet \u70b9\u4e91\u573a\u666f\u3002\u7531\u4e8e\u610f\u56fe\u8868\u8fbe\u7684\u591a\u6837\u6027\uff0c\u4f7f\u7528\u9884\u5b9a\u4e49\u683c\u5f0f\u8fdb\u884c\u6807\u6ce8\u4f1a\u9650\u5236\u6a21\u578b\u7684\u6cdb\u5316\u80fd\u529b\u3002\u6b64\u5916\uff0c\u4f17\u5305\u6807\u6ce8\u5f80\u5f80\u7f3a\u4e4f\u53ef\u9760\u6027\uff0c\u800c\u4e13\u4e1a\u6807\u6ce8\u6210\u672c\u9ad8\u4e14\u96be\u4ee5\u6269\u5c55\u3002\u56e0\u6b64\uff0c\u5982\u56fe\u4e8c\u6240\u793a\uff0c\u6211\u4eec\u91c7\u7528 GPT-4 \u751f\u6210\u610f\u56fe\u6587\u672c\uff0c\u5e76\u7ecf\u4eba\u5de5\u8d28\u91cf\u68c0\u67e5\uff0c\u786e\u4fdd\u9ad8\u51c6\u786e\u6027\u548c\u591a\u6837\u6027\u3002<\/p>\n

    \"\"<\/p>\n

    \u56fe\u4e8c\uff1a\uff08\u4e0a\u6392\uff09\u6570\u636e\u96c6\u6784\u5efa\u6d41\u7a0b\u56fe\u3002\u6784\u5efa\u573a\u666f\u56fe\u540e\uff0c\u6211\u4eec\u6839\u636e\u4e09\u4e2a\u6807\u51c6\u9009\u62e9\u5bf9\u8c61\uff1a\u5e38\u89c1\u5bf9\u8c61\u3001\u975e\u5e73\u51e1\u5bf9\u8c61\u3001\u65e0\u6b67\u4e49\u5bf9\u8c61\u3002\u6211\u4eec\u4f7f\u7528 ChatGPT \u6839\u636e\u6211\u4eec\u8bbe\u8ba1\u7684\u63d0\u793a\u751f\u6210\u610f\u56fe\u6587\u672c\u3002\u6700\u540e\uff0c\u6211\u4eec\u624b\u52a8\u6e05\u7406\u6570\u636e\u3002\uff08\u4e0b\u6392\uff09\u6211\u4eec\u7684\u6570\u636e\u96c6\u4e2d\u9488\u5bf9\u4e0d\u540c\u76ee\u6807\u6570\u91cf\u548c\u6587\u672c\u957f\u5ea6\u7684\u793a\u4f8b\u3002<\/p>\n

    \u5176\u6b21\uff0c\u4e3a\u4e86\u5145\u5206\u8bc4\u4f30\u6211\u4eec\u76ee\u524d\u89e3\u51b3\u8fd9\u4e2a\u95ee\u9898\u7684\u7814\u7a76\u80fd\u529b\uff0c\u6211\u4eec\u4f7f\u7528\u4e09\u79cd\u4e3b\u8981\u7684\u57fa\u4e8e\u8bed\u8a00\u7684 3D \u76ee\u6807\u68c0\u6d4b\u6280\u672f\u4e3a\u6211\u4eec\u7684\u57fa\u51c6\u6784\u5efa\u4e86\u51e0\u4e2a\u57fa\u7ebf\u3002\u8fd9\u6d89\u53ca\u4f7f\u7528\u4ee5\u4e0b\u6a21\u578b\u8bc4\u4f30\u6211\u4eec\u7684\u6570\u636e\u96c6\uff1a\u4e13\u95e8\u4e3a 3D \u89c6\u89c9\u5b9a\u4f4d\u8bbe\u8ba1\u7684\u4e13\u5bb6\u6a21\u578b\uff08BUTD-DETR, EDA\uff09\u3001\u4e3a\u901a\u7528 3D \u7406\u89e3\u4efb\u52a1\u5236\u5b9a\u7684\u57fa\u7840\u6a21\u578b\uff083D-VisTA\uff09\u4ee5\u53ca\u57fa\u4e8e\u5927\u578b\u8bed\u8a00\u6a21\u578b (LLM) \u7684\u6a21\u578b\uff08Chat-3D-v2\uff09\u3002\u6211\u4eec\u4f7f\u7528\u591a\u79cd\u8bbe\u7f6e\u8bc4\u4f30\u8fd9\u4e9b\u57fa\u7ebf\uff0c\u5373\u4ece\u5934\u5f00\u59cb\u8bad\u7ec3\u3001\u5fae\u8c03\u548c\u96f6\u6837\u672c\u3002<\/p>\n

    \u65b9\u6cd5<\/h4>\n

    \u5982\u4f55\u89e3\u51b3 3D \u610f\u56fe\u5b9a\u4f4d\u95ee\u9898\uff1f<\/strong><\/p>\n

    \u5982\u56fe\u4e09\u6240\u793a\uff0c\u6211\u4eec\u8bbe\u8ba1\u4e86\u4e00\u79cd\u65b0\u65b9\u6cd5 IntentNet\uff0c\u7ed3\u5408\u591a\u4e2a\u5173\u952e\u6280\u672f\uff1a<\/p>\n

      \n
    • \u52a8\u5bbe\u5bf9\u9f50\uff08Verb-Object Alignment\uff09\uff1a\u5148\u8bc6\u522b\u610f\u56fe\u4e2d\u7684\u52a8\u8bcd\uff0c\u518d\u4e0e\u76f8\u5e94\u5bbe\u8bed\u7279\u5f81\u8fdb\u884c\u5bf9\u9f50\uff0c\u63d0\u9ad8\u610f\u56fe\u7406\u89e3\u80fd\u529b\u3002<\/li>\n
    • \u5019\u9009\u6846\u5339\u914d\uff08Candidate Box Matching\uff09\uff1a\u5728\u7a00\u758f 3D \u70b9\u4e91\u4e2d\u663e\u5f0f\u5339\u914d\u5019\u9009\u76ee\u6807\u6846\uff0c\u63d0\u9ad8\u591a\u6a21\u6001\u610f\u56fe\u63a8\u7406\u80fd\u529b\u3002<\/li>\n
    • \u7ea7\u8054\u81ea\u9002\u5e94\u5b66\u4e60\uff08Cascaded Adaptive Learning\uff09\uff1a\u6839\u636e\u4e0d\u540c\u635f\u5931\u51fd\u6570\u7684\u4f18\u5148\u7ea7\uff0c\u81ea\u9002\u5e94\u8c03\u6574\u635f\u5931\u51fd\u6570\u6743\u91cd\uff0c\u63d0\u5347\u6a21\u578b\u6027\u80fd\u3002<\/li>\n<\/ul>\n

      \"\"<\/p>\n

      \u56fe\u4e09\uff1aIntentNet\uff1a\uff08\u9aa8\u5e72\u7f51\u7edc\uff09PointNet++ \u7528\u4e8e\u63d0\u53d6\u70b9\u7279\u5f81\uff1bMLP \u7f16\u7801 3D \u76ee\u6807\u68c0\u6d4b\u5668\u9884\u6d4b\u7684\u6846\uff1bRoBERTa \u7f16\u7801\u6587\u672c\u8f93\u5165\u3002\uff08\u7f16\u7801\u5668\uff09\u57fa\u4e8e\u6ce8\u610f\u529b\u7684\u5757\u7528\u4e8e\u591a\u6a21\u6001\u878d\u5408\uff0c\u901a\u8fc7\u4e0e\u6587\u672c\u7279\u5f81\u7684\u96c6\u6210\u6765\u589e\u5f3a\u6846\u7279\u5f81\u3002\uff08\u89e3\u7801\u5668\uff09\u5177\u6709\u6700\u9ad8\u7f6e\u4fe1\u5ea6\u7684\u524d k \u4e2a\u70b9\u7279\u5f81\u88ab\u9009\u62e9\u4e3a\u63d0\u51fa\u7684\u67e5\u8be2\uff08query\uff09\uff0c\u7136\u540e\u901a\u8fc7\u57fa\u4e8e\u6ce8\u610f\u529b\u7684\u5757\u8fdb\u884c\u66f4\u65b0\u3002\u51e0\u4e2a MLP \u7528\u4e8e\u7ebf\u6027\u6295\u5f71\u67e5\u8be2\uff0c\u4ee5\u4fbf\u8fdb\u884c\u540e\u7eed\u7684\u635f\u5931\u8ba1\u7b97\u3002\uff08\u635f\u5931\u51fd\u6570\uff09\u8be5\u6a21\u578b\u5b66\u4e60\u4f7f\u7528 L_bce \u5c06\u5019\u9009\u6846\u4e0e\u76ee\u6807\u5bf9\u8c61\u8fdb\u884c\u5339\u914d\uff1b\u67e5\u8be2\uff08query\uff09\u88ab\u8bad\u7ec3\u4ee5\u8bc6\u522b\u52a8\u8bcd (L_vPos)\uff0c\u4e0e\u52a8\u8bcd\u5bf9\u9f50 (L_vSem)\uff0c\u5e76\u4e0e\u5bbe\u8bed\u5bf9\u9f50 (L_voSem)\u3002<\/p>\n

      \u5b9e\u9a8c<\/h4>\n

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