Multimedia Laboratory

Time 2020-09-28 10:03:49

Web Name: Multimedia Laboratory

WebSite: http://mmlab.ie.cuhk.edu.hk

ID:62702

Keywords:

Multimedia,Laboratory,

Description:

OpenMMLab Project The OpenMMLab project aims at building high-quality open-source toolboxes for several important research areas, including object detection, action recognition, etc. Read More Face Analysis MMLAB develops novel algorithms for automatically detecting faces, locating facial keypoints, aligning face images, and identifying or verifying a person from a digital image or a video stream. Read More Person Analysis Automatically understanding the behaviors of crowd from video sequences is of great interest to the computer vision community, and has drawn more and more attentions in recent years. It has important applications to event recognition, traffic flow estimation, behavior prediction, abnormality detection, and crowd simulation. Read More Detection and Segmentation Our research includes object detection, semantic segmentation, instance segmentation. Read More Low-level Vision MMLAB develops efficient and effective algorithms that improve image and video qualities. We dedicate to enhance the world we see. Read More The CUHK Multimedia Lab (MMLab) is one of the pioneering institutes on deep learning. In GPU Technology Conference (GTC) 2016, a world-wide technology summit, our lab is recognized as one of the top ten AI pioneers, and listed together with top research groups in the world (e.g. MIT, Stanford, Berkeley, and Univ. of Toronto). Today, we remain one of the most active research labs in computer vision deep learning, publishing over 40 papers on top conferences (CVPR/ICCV/ECCV/NIPS) every year. Our lab has a large group of talented students, plenty of computational resources, and steady financial support, and free research environment. The Multimedia Laboratory of the Department of Information Engineering is established by Prof. Xiaoou Tang in July 2001. We won the CVPR 2009 Best Paper Award. This is the first one ever from Asia. Read more K. He, J. Sun, and X. Tang, "Single Image Haze Removal Using Dark Channel Prior ," CVPR, 2009 Best paper awards by our lab's alumni: Dahua Lin with his paper "Construction of Dependent Dirichlet Processes based on Poisson Processes", NIPS, 2010 Dong Xu with his paper "Visual Event Recognition in Videos by Learning from Web Data", CVPR, 2010 Huan Wang with his paper "Exact Recovery of Sparsely-Used Dictionaries", COLT, 2012 Shuicheng Yan with his papers "Dynamic Captioning: Video Accessibility Enhancement for Hearing Impairment" in ACM MM, 2010; "Automated Assembly of Shredded Pieces from Multiple Photos" in ICME, 2010; "Wow! You Are So Beautiful Today!", ACM MM, 2013; "Attributes-augmented Semantic Hierarchy for Image Retrieval", ACM MM, 2013 We organize the second WIDER Face and Person Challenge in conjunction with ICCV 2019. There are four exciting tracks with great prizes. Deadline of challenge: July 25, 2019. 05/2019 NTIRE 2019 winner Our new video restoration method, EDVR, won all four tracks in the NTIRE 2019 video restoration and enhancement challenges. 02/2019 CVPR 2019 We have 33 papers (7 oral) accepted to CVPR 2019. 12/2018 ICLR 2019 Our lab have 3 papers accepted to ICLR 2019. 11/2018 AAAI 2019 Our lab have 6 papers (4 oral and 1 spotlight) accepted to AAAI 2019. 09/2018 COCO 2018 Challenge Winner Our team MMDet wins the COCO 2018 Challenge (object detection/instance segmentation track). Codebase is released. 09/2018 NeurIPS 2018 Our lab have 5 papers accepted to NeurIPS 2018. 07/2018 ECCV 2018 Our lab have 26 papers accepted to ECCV 2018. 02/2018 CVPR 2018 Our lab have 28 papers (1 oral and 7 spotlight) accepted to CVPR 2018. All news This site was built using Bootstrap, a front-end framework for web development. Thanks to the following site developers and all lab members that contribute their suggestions and information

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