{"id":595,"date":"2020-03-10T00:13:18","date_gmt":"2020-03-09T15:13:18","guid":{"rendered":"https:\/\/www.ai-gakkai.or.jp\/jsai2020\/?page_id=595"},"modified":"2020-07-13T00:11:57","modified_gmt":"2020-07-12T15:11:57","slug":"invited-talk","status":"publish","type":"page","link":"https:\/\/www.ai-gakkai.or.jp\/jsai2020\/invited-talk","title":{"rendered":"\u57fa\u8abf\u8b1b\u6f14\u30fb\u62db\u5f85\u8b1b\u6f14\u30fb\u7279\u5225\u8b1b\u6f14"},"content":{"rendered":"

\u57fa\u8abf\u8b1b\u6f14<\/h3>\n

6\u67089\u65e5\uff08\u706b\uff09<\/span>\u300010:30\uff5e11:40\u3000A\u4f1a\u5834\uff084F 5F 6F \u30e1\u30a4\u30f3\u30db\u30fc\u30eb\uff20\u718a\u672c\u57ce\u30db\u30fc\u30eb\uff09<\/span><\/p>\n

\u300cAI\u6280\u8853\u3092\u6d3b\u7528\u3059\u308b\u793e\u4f1a\u306e\u30c7\u30b6\u30a4\u30f3\u300d<\/span><\/h4>\n
\n\"\"<\/p>\n

\u4e2d\u5cf6 \u79c0\u4e4b \u6c0f<\/span>
\uff08\u672d\u5e4c\u5e02\u7acb\u5927\u5b66 \u5b66\u9577\uff09<\/p>\n<\/div>\n

AI\u7814\u7a76\u306e\u6b74\u53f2\u4e0a\u521d\u3081\u3066\uff0c\u305d\u306e\u6280\u8853\u304c\u5b9f\u7528\u5316\u3055\u308c\u308b\u3088\u3046\u306b\u306a\u3063\u305f\uff0e\u3057\u304b\u3082\u30a8\u30af\u30b9\u30dd\u30cd\u30f3\u30b7\u30e3\u30eb\u6280\u8853\u3068\u3082\u547c\u3070\u308c\u308b\u3088\u3046\u306b\u305d\u306e\u767a\u5c55\u306f\u6025\u901f\u3067\u3042\u308b\uff0e\u3057\u304b\u3057\u306a\u304c\u3089\u305d\u308c\u3092\u53d7\u3051\u5165\u308c\u308b\u793e\u4f1a\u306e\u5074\u306f\u4e00\u5411\u306b\u5909\u308f\u3063\u3066\u3044\u306a\u3044\u3088\u3046\u306b\u601d\u3048\u308b\uff0e\u69d8\u3005\u306a\u793e\u4f1a\u5236\u5ea6\u306f\u53e4\u3044\u6cd5\u898f\u5236\u306e\u4e0b\u3067\u5909\u5316\u3057\u3066\u3044\u306a\u3044\uff0e\u300c\u30bd\u30b5\u30a8\u30c6\u30a35.0\u300d\u306e\u547c\u3073\u540d\u304c\u51fa\u3066\u304b\u3089\u6570\u5e74\u304c\u305f\u3064\u304c\uff0c\u305d\u306e\u5b9f\u4f53\u5316\u306f\u884c\u308f\u308c\u3066\u3044\u306a\u3044\uff0e\u672c\u8b1b\u6f14\u3067\u306fAI\u306e\u53ef\u80fd\u6027\u3092\u793a\u3057\uff0c\u65b0\u3057\u3044\u793e\u4f1a\u306e\u30c7\u30b6\u30a4\u30f3\u3092\u8003\u3048\u308b\uff0e\u307e\u305f\uff0c\u305d\u308c\u3092\u5b9f\u73fe\u3059\u308b\u305f\u3081\u306b\u5fc5\u8981\u306a\u4eca\u5f8c\u306eAI\u7814\u7a76\u306e\u5728\u308a\u65b9\u306b\u3064\u3044\u3066\u3082\u8a00\u53ca\u3059\u308b\uff0e<\/p>\n

[ \u7565\u6b74 ]
1983\u5e74\u6771\u4eac\u5927\u5b66\u60c5\u5831\u5de5\u5b66\u5c02\u9580\u8ab2\u7a0b\u4fee\u4e86\uff08\u5de5\u5b66\u535a\u58eb\uff09\uff0e\u540c\u5e74\u96fb\u7dcf\u7814\u5165\u6240\uff0e2001\u5e74\u7523\u7dcf\u7814\u30b5\u30a4\u30d0\u30fc\u30a2\u30b7\u30b9\u30c8\u7814\u7a76\u30bb\u30f3\u30bf\u30fc\u9577\uff0e2004\u5e74\u3088\u308a2016\u5e74\u307e\u3067\u516c\u7acb\u306f\u3053\u3060\u3066\u672a\u6765\u5927\u5b66\u5b66\u9577\u304a\u3088\u3073\u7406\u4e8b\u9577\u6b74\u4efb\uff0e2016\u5e74\u540c\u540d\u8a89\u5b66\u9577\u306a\u3089\u3073\u306b\u6771\u4eac\u5927\u5b66\u5927\u5b66\u9662\u60c5\u5831\u7406\u5de5\u5b66\u7cfb\u7814\u7a76\u79d1\u5148\u7aef\u4eba\u5de5\u77e5\u80fd\u5b66\u6559\u80b2\u5bc4\u4ed8\u8b1b\u5ea7 \u7279\u4efb\u6559\u6388\uff0e2018\u5e744\u6708\u3088\u308a\u516c\u7acb\u5927\u5b66\u6cd5\u4eba\u672d\u5e4c\u5e02\u7acb\u5927\u5b66\u7406\u4e8b\u9577\u304a\u3088\u3073\u5b66\u9577\u5c31\u4efb\uff0e\u682a\u5f0f\u4f1a\u793e\u672a\u6765\u30b7\u30a7\u30a2\u53d6\u7de0\u5f79\u4f1a\u9577\uff0e2019\u5e7410\u6708\u300c\u60c5\u5831\u5316\u4fc3\u9032\u8ca2\u732e\u500b\u4eba\u7b49\u8868\u5f70\u300d\u7d4c\u6e08\u7523\u696d\u5927\u81e3\u8cde\u3092\u53d7\u8cde\uff0e<\/p>\n

[ \u8b1b\u6f14\u52d5\u753b<\/span> ] \u203b7\u670812\u65e5\u3067\u52d5\u753b\u306b\u306f\u30a2\u30af\u30bb\u30b9\u3067\u304d\u306a\u304f\u306a\u308a\u307e\u3059\uff0e<\/p>\n

\u62db\u5f85\u8b1b\u6f14<\/h3>\n

6\u670810\u65e5\uff08\u6c34\uff09<\/span>\u300011:00\uff5e12:10\u3000A\u4f1a\u5834\uff084F 5F 6F \u30e1\u30a4\u30f3\u30db\u30fc\u30eb\uff20\u718a\u672c\u57ce\u30db\u30fc\u30eb\uff09<\/span><\/p>\n

\u300c\u4eba\u9593\u306e\u77e5 \u6a5f\u68b0\u306e\u77e5\u300d<\/span><\/h4>\n
\n\"\"<\/p>\n

\u690d\u7530 \u4e00\u535a \u6c0f<\/span>
\uff08\u6771\u4eac\u5927\u5b66 \u6559\u6388\uff09<\/p>\n<\/div>\n

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[ \u7565\u6b74 ]
1988\u5e74\u6771\u4eac\u5927\u5b66\u6559\u990a\u90e8\u5352\u696d\uff0c1993\u540c\u5927\u5b66\u9662\u7dcf\u5408\u6587\u5316\u7814\u7a76\u79d1\u535a\u58eb\u8ab2\u7a0b\u4fee\u4e86\uff0c1994\u5e74\u540c\u5927\u5b66\u9662\u52a9\u624b\uff0c1999\u5e74\u540c\u5927\u5b66\u9662\u52a9\u6559\u6388\uff0c2007\u5e74\u540c\u5927\u5b66\u9662\u51c6\u6559\u6388\u3092\u7d4c\u3066\uff0c2010\u5e744\u6708\u3088\u308a\u540c\u5927\u5b66\u9662\u6559\u6388\uff0c\u73fe\u5728\u306b\u81f3\u308b\uff0e
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[ \u8b1b\u6f14\u8cc7\u6599PDF\u30c0\u30a6\u30f3\u30ed\u30fc\u30c9<\/a> ]<\/p>\n

\u62db\u5f85\u8b1b\u6f14<\/h3>\n

6\u670811\u65e5\uff08\u6728\uff09<\/span>\u300011:00\uff5e12:10\u3000A\u4f1a\u5834\uff084F 5F 6F \u30e1\u30a4\u30f3\u30db\u30fc\u30eb\uff20\u718a\u672c\u57ce\u30db\u30fc\u30eb\uff09<\/span><\/p>\n

\u300cLearning Beyond 2D Images\u300d<\/span><\/h4>\n
\n\"\"<\/p>\n

Winston Hsu \u6c0f<\/span>
\uff08National Taiwan University \/ Professor\uff09<\/p>\n<\/div>\n

We observed super-human capabilities from current (2D) convolutional networks for the images — either for discriminative or generative models. For this talk, we will show our recent attempts in visual cognitive computing beyond 2D images. We will first demonstrate the huge opportunities as augmenting the leaning with temporal cues, 3D (point cloud) data, raw data, audio, etc. over emerging domains such as entertainment, security, healthcare, manufacturing, etc. In an explainable manner, we will justify how to design neural networks leveraging the novel (and diverse) modalities. We will demystify the pros and cons for these novel signals. We will showcase a few tangible applications ranging from video QA, robotic object referring, situation understanding, autonomous driving, etc. We will also review the lessons we learned as designing the advanced neural networks which accommodate the multimodal signals in an end-to-end manner.<\/p>\n

[ \u7565\u6b74 ]
Prof. Winston Hsu is an active researcher dedicated to large-scale image\/video retrieval\/mining, visual recognition, and machine intelligence. He is a Professor in the Department of Computer Science and Information Engineering, National Taiwan University and co-leads Communication and Multimedia Lab (CMLab). He and his team have been recognized with technical awards in multimedia and computer vision research communities including IBM Research Pat Goldberg Memorial Best Paper Award (2018), Best Brave New Idea Paper Award in ACM Multimedia 2017, First Place for IARPA Disguised Faces in the Wild Competition (CVPR 2018), Third Place (mini-track) for Moments in Time Challenge (video action recognition) in CVPR 2018,Third Place for 2018 IEEE Signal Processing Society Video and Image Processing (VIP) Cup, First Prize in ACM Multimedia Grand Challenge 2011, First Place in MSR-Bing Image Retrieval Challenge 2013, ACM Multimedia 2013\/2014 Grand Challenge Multimodal Award, \u00a0ACM Multimedia 2006 Best Paper Runner-Up, etc.
Prof. Hsu is keen to realizing advanced researches towards business deliverables via academia-industry collaborations and co-founding startups. Working closely with the industry, he was a Visiting Scientist at Microsoft Research Redmond (2014) and had his 1-year sabbatical leave (2016-2017) at IBM TJ Watson Research Center, New York, to enhance Watson’s visual cognition, where he contributed the first AI produced movie trailer. He is the Founding Director for NVIDIA AI Lab (NTU), the 1st in Asia. He received Ph.D. (2007) from Columbia University, New York. Before that, he was a founding engineer and research manager in CyberLink Corp. He serves as the Associate Editor for IEEE Transactions on Circuits and Systems for Video Technology (TCSVT) and IEEE Transactions on Multimedia, two premier journals, and was in the Editorial Board for IEEE Multimedia Magazine (2010 – 2017). He also co-organized several premier conferences such as ACM Multimedia, ACCV, ICME, ICMR, ICIP, etc.<\/p>\n

\u7279\u5225\u8b1b\u6f14<\/h3>\n

6\u67089\u65e5\uff08\u706b\uff09<\/span>\u300017:20\uff5e18:30\u3000A\u4f1a\u5834\uff084F 5F 6F \u30e1\u30a4\u30f3\u30db\u30fc\u30eb\uff20\u718a\u672c\u57ce\u30db\u30fc\u30eb\uff09<\/span><\/p>\n

\u300cAI\u6280\u8853\u306e\u718a\u672c\u57ce\u5fa9\u8208\u3078\u306e\u5fdc\u7528\u300d<\/span><\/h4>\n
\n\"\"<\/p>\n

\u4e0a\u7027 \u525b \u6c0f<\/span>
\uff08\u718a\u672c\u5927\u5b66 \u51c6\u6559\u6388\uff09<\/p>\n<\/div>\n

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