\u8cc7\u8a0a\u7ba1\u7406\u7cfb\u8a31\u5fd7\u4ef2\u52a9\u7406\u6559\u6388\u5e36\u9818\u7684\u524d\u77bb\u8996\u89ba\u5be6\u9a57\u5ba4 (Advanced Computer Vision Laboratory, ACVLab) \uff0c\u57f9\u990a\u540c\u5b78\u5229\u7528\u8cc7\u8a0a\u7ba1\u7406\u6280\u80fd\uff0c\u9806\u61c9AI\u767c\u5c55\u8da8\u52e2\uff0c\u5c07\u96fb\u8166\u8996\u89ba\u8207\u6df1\u5ea6\u5b78\u7fd2\u5169\u5927\u9762\u5411\u5c0e\u5165\u6559\u5b78\uff0c\u63d0\u5347\u540c\u5b78\u5728\u8edf\u9ad4\u8a2d\u8a08\u8207\u6642\u4e8b\u654f\u92b3\u5ea6\uff0c\u8a2d\u8a08\u51fa\u773e\u591a\u76ca\u65bc\u7db2\u8def\u793e\u7fa4\u4ee5\u53ca\u751f\u6d3b\u61c9\u7528\u7684\u5c08\u696d\u7a0b\u5f0f\u3002\u8cc7\u7ba1\u7cfb\u5927\u4e09\u674e\u4fca\u6bc5\u540c\u5b78\u3001\u5433\u7d39\u6c11\u540c\u5b78\u53c3\u52a0\u591a\u5a92\u9ad4\u9818\u57df\u570b\u969b\u9802\u5c16\u6703\u8b70ACM Multimedia 2019\u6240\u8209\u8fa6\u7684Social Media Prediction Challenge(SMPC)\u7af6\u8cfd\u7372\u4e16\u754c\u51a0\u8ecd\u3002\u66fe\u6587\u6d77\u8207\u694a\u7693\u73fd\u540c\u5b78\uff0c\u53c3\u52a0\u96fb\u8166\u8996\u89ba\u9818\u57df\u6700\u9802\u5c16\u6703\u8b70IEEE ICCV \u4e2d\u81ea\u99d5\u8eca\u7684\u9810\u6e2c\u7af6\u8cfd\u7372\u4e16\u754c\u7b2c\u4e09\u540d\u7684\u4f73\u7e3e\u3002\u78a9\u4e8c\u7814\u7a76\u751f\u838a\u6613\u4fee\uff0c\u57282019\u570b\u969b\u4e0a\u5f71\u50cf\u8655\u7406\u9818\u57df\u9802\u5c16\u7814\u8a0e\u6703 IEEE ICIP \u4e2d\u7372ICIP\u6700\u4f73\u5b78\u751f\u8ad6\u6587\u734e\uff0c\u6210\u70ba\u672c\u5e74\u5ea6ICIP\u552f\u4e00\u7372\u5f97\u5b78\u8853\u734e\u9805\u4e4b\u53f0\u7063\u5718\u968a\u3002\u5176\u7814\u7a76\u5ba4\u512a\u7570\u6210\u679c\u7d71\u8a08\u81f3\u4eca\u5b78\u751f\u5206\u5225\u5728\u570b\u969b\u5404\u985e\u7af6\u8cfd\u7372\u5f976\u6b21\u53ca\u570b\u5167\u7af6\u8cfd\u7372\u5f972\u6b21\u7684\u512a\u826f\u6210\u7e3e\u6b8a\u69ae\u3002
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\u8cc7\u8a0a\u7ba1\u7406\u7cfb\u524d\u77bb\u8996\u89ba\u5be6\u9a57\u5ba4 (ACVLab) \u57f9\u80b2\u540c\u5b78\u53c3\u8207\u570b\u5916\u8cfd\u4e8b\u4e26\u4ee5\u300c\u4eba\u5de5\u667a\u6167\u300d\u8207\u300c\u6df1\u5ea6\u5b78\u7fd2\u300d\u76f8\u95dc\u7684\u7af6\u8cfd\u5c62\u7372\u4f73\u7e3e\u3002ACVLab\u4e3b\u8981\u7814\u7a76\u65b9\u5411\u5206\u70ba\u300c\u96fb\u8166\u8996\u89ba (Computer Vision) \u300d\u7d50\u5408\u300c\u6df1\u5ea6\u5b78\u7fd2 (Deep Learning)\u300d \u4e4b\u76f8\u95dc\u61c9\u7528\uff0c\u4f8b\u5982\u300c\u81ea\u99d5\u99db (Autonomous Driving) \u8996\u89ba\u8f14\u52a9\u7cfb\u7d71\u300d\u3001\u300c\u507d\u9020\u5f71\u50cf\u7684\u8fa8\u8b58 (Fake Image Detection)\u300d\u3001\u300c\u8eca\u8f1b\u91cd\u8b58\u5225 (Vehicle Re-identification)\u300d\u3001\u300c\u8eca\u8f1b\u5075\u6e2c (Vehicle Detection)\u300d\u3001\u300c\u793e\u7fa4\u5a92\u9ad4\u9ede\u64ca\u7387\u9810\u6e2c (Social Media Popularity Prediction)\u300d\u3001\u4ee5\u53ca\u300c\u5f71\u50cf\u8d85\u89e3\u6790\u5ea6 (Image Super-Resolution) \u300d\u7b49\uff0c\u900f\u904e\u5c08\u696d\u5b78\u7fd2\u8207\u5be6\u969b\u53c3\u8207\u570b\u969b\u8cfd\u4e8b\uff0c\u7df4\u5c31\u4e00\u8eab\u597d\u672c\u9818\u3002
\u8cc7\u7ba1\u7cfb\u5927\u4e09\u674e\u4fca\u6bc5\u540c\u5b78\u3001\u5433\u7d39\u6c11\u540c\u5b78\u53c3\u52a0\u7684SMPC\u7af6\u8cfd\u4e3b\u8981\u4ee5\u5927\u91cf\u793e\u7fa4\u5a92\u9ad4\u7684\u7d71\u8a08\u8cc7\u6599\u3001\u7167\u7247\u8207\u5176EXIF\u7b49\u7d30\u7bc0\uff0c\u63a1\u7528\u300c\u9ad8\u968e\u8207\u4e2d\u968e\u8a9e\u610f\u8cc7\u8a0a (High- and Middle-level Semantic Features)\u300d \u8207\u300cMeta-data\u300d\u7814\u767c\u51fa\u4e86\u4e00\u5957\u300cMultimodal Feature Mining (MFM) \u6280\u8853\u300d\uff0c\u53ef\u540c\u6642\u63a2\u7d22\u4e0d\u540c\u7a2e\u985e\u7684\u8cc7\u6599\u7279\u5fb5\uff0c\u9032\u800c\u7cbe\u6e96\u9810\u6e2c\u51fa\u767c\u6587\u7684\u9ede\u64ca\u7387\u3002\u82e5\u80fd\u9748\u6d3b\u904b\u7528\u6b64\u6280\u8853\uff0c\u5ee3\u544a\u516c\u53f8\u4fbf\u53ef\u4ee5\u8f15\u6613\u7684\u627e\u51fa\u5177\u6709\u6f5b\u5728\u71b1\u9580\u6587\u7ae0\u9810\u6e2c\u51fa\u4f86\uff0c\u5c07\u5ee3\u544a\u7f6e\u5165\uff0c\u4e14\u6700\u5927\u5316\u5176\u6536\u76ca\u7a0b\u5ea6\u3002
\u5c08\u984c\u751f\u66fe\u6587\u6d77\u8207\u694a\u7693\u73fd\u540c\u5b78\uff0c\u53c3\u52a0\u96fb\u8166\u8996\u89ba\u9818\u57df\u6700\u9802\u5c16\u6703\u8b70IEEE ICCV \u4e2d\u81ea\u99d5\u8eca\u7684\u9810\u6e2c\u7af6\u8cfd\uff0c\u904b\u7528\u6280\u8853\u958b\u767c\u51fa\u4e00\u7a2e\u300c\u5feb\u901f\u524d\u994b\u795e\u7d93\u7db2\u8def (Feed-Forward Deep Neural Network)\u300d\u4f86\u64f7\u53d6\u6642\u9593\u8ef8\u7684\u8cc7\u8a0a\uff0c\u89e3\u6c7a\u8a08\u7b97\u8907\u96dc\u5ea6\u904e\u9ad8\u7684\u554f\u984c\u53ca\u767c\u5c55\u4e00\u5957\u300c\u591a\u6a21\u8a08\u7b97\u6a21\u7d44 (Multimodal Computing Module) \u300d\u5feb\u901f\u4e14\u7cbe\u6e96\u7684\u9810\u6e2c\u4e0b\u4e00\u79d2\u81ea\u99d5\u8eca\u7684\u65b9\u5411\u76e4\u89d2\u5ea6\u8207\u6cb9\u9580\u901f\u5ea6\uff0c\u9664\u69ae\u7372\u4e16\u754c\u7b2c\u4e09\u540d\u7684\u4f73\u7e3e\u5916\uff0c\u66f4\u7372\u9080\u5230\u6703\u8b70\u6f14\u8b1b\u4ea4\u6d41\uff0c\u8b93\u4e16\u754c\u770b\u898b\u5c4f\u79d1\u7684\u5be6\u529b\u3002\u53e6\u5916ACVLab\u7684\u78a9\u4e8c\u7814\u7a76\u751f\u838a\u6613\u4fee\u7814\u7a76\u80fd\u91cf\u4e5f\u662f\u4e16\u754c\u9802\u5c16\uff0c\u57282019\u570b\u969b\u4e0a\u5f71\u50cf\u8655\u7406\u9818\u57df\u9802\u5c16\u7814\u8a0e\u6703 IEEE ICIP \u4e2d\uff0c\u57f7\u884c\u8a31\u5fd7\u4ef2\u8001\u5e2b\u4e4b\u79d1\u6280\u90e8\u8a08\u756b\u4e4b\u7814\u7a76\u6210\u679c-\u300c\u507d\u9020\u4eba\u81c9\u5f71\u50cf\u4e4b\u5075\u6e2c\u300d\u7372\u5f97\u63a5\u53d7\u4e14\u8a55\u9078\u70ba\u53e3\u982d\u8ad6\u6587\u767c\u8868\uff0c\u66f4\u5728\u591a\u90542071\u7bc7\u8ad6\u6587\u6295\u7a3f\u4e2d\u7372\u5f97\u300cICIP\u6700\u4f73\u5b78\u751f\u8ad6\u6587\u734e (Best Student Paper Award)\u300d\uff0c\u6210\u70ba\u672c\u5e74\u5ea6ICIP\u552f\u4e00\u7372\u5f97\u5b78\u8853\u734e\u9805\u4e4b\u53f0\u7063\u5718\u968a\u3002
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\u5ef6\u4f38\u95b1\u8b80<\/p>\n\n\n\n
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