What's New in LV

• NUS-Qihoo 360 Joint Lab Achieved NO. 1 on ILSVRC 2017 Object Localization Task!

  NUS-Qihoo 360 Joint Lab achieved NO. 1 on ILSVRC 2017 Object Localization Task, with all competition tasks within Top 3! This project is collaborated by NUS LV group (Yunpeng Chen, Jianan Li, Yunchao Wei, Huaxin Xiao, Jianshu Li, Mengdan Zhang, Xuecheng Nie, Xiaojie Jin, Jiashi Feng) and Qihoo 360 AI institute (Jian Dong, Shuicheng Yan). See the ILSVRC 2017 official website for official leaderboard. [20/07/2017]

• LV Team Achieved NO. 1 on MS-Celeb-1M Large-Scale Face Recognition Hard Set / Random Set / Low-Shot Learning Challenge!

  The LV team achieved the top performance on the ICCV 2017 MS-Celeb-1M Large-Scale Face Recognition Hard Set / Random Set / Low-Shot Learning Challenge! This project is collaborated by NUS LV group (Feng Jiashi, Zhao Jian, Wang Zhecan) and Panasonic R&D Center Singapore (Shen Shengmei, Xu Yan, Cheng Yu, Xiong Lin, Jayashree Karlekar, Sugiri Pranata), outperforming the 2nd-best by a large margin. See the MS-Celeb-1M official website for official leaderboard. [19/07/2017]

• LV Team Achieved NO. 2 on CVPR 2017 Visual Understanding of Humans in Crowd Scene & the 1st Look into Person (LIP) Challenge Human Parsing/Pose Task!

  The LV team achieved the top-2 performance on the CVPR 2017 Visual Understanding of Humans in Crowd Scene & the 1st Look into Person (LIP) Challenge Human Parsing and Pose Task! This project is supervised by Prof. Yan Shuicheng, collaborated by Zhao Jian, Nie Xuecheng, Xiao Huaxin, Chen Yunpeng, Li Jianshu, (the first three authors are with equal contributions), outperforming the 3rd-best by a large margin. See the CVPR 2017 official website for details. [05/06/2017]

• LV Team Achieved NO. 1 on IJB-A Face Verification/Identification Challenge!

  The LV team achieved the top performance on the National Institute of Standards and Technology (NIST) 2017 IARPA Janus Benchmark A (IJB-A) Face Verification Challenge and Face Identification Challenge!

  This project is collaborated by NUS LV group (Feng Jiashi, Zhao Jian) and Panasonic R&D Center Singapore (Shen Shengmei, Xiong Lin, Jayashree Karlekar, Sugiri Pranata), outperforming the 2nd-best by a large margin. See the NIST official website for official report. We also release a technical report on arxiv titled "A Good Practice Towards Top Performance of Face Recognition: Transferred Deep Feature Fusion". [26/04/2017]

• MMM 16: Winner of Best Student Paper Award

  The paper "Computational Face Reader" by Xiangbo Shu, Liyan Zhang, Jinhui Tang, Guo-Sen Xie, and Shuicheng Yan, won the Best Student Paper Award in the 22nd Anniversary International Conference on MultiMedia Modeling held in Miami, USA during Jan 4 -- Jan 6, 2016. [08/01/2016]