activity
20152023
most citedEvaluating Two-Stream CNN for Video Classification

114 citations · 462 across the 40 of their papers we have counts for

collaborators
Showing 2017Show all

7 papers · 1 filter

cs.CV2017★ 6 cited

DeepSkeleton: Skeleton Map for 3D Human Pose Regression

Qingfu Wan, Wei Zhang, Xiangyang Xue

Despite recent success on 2D human pose estimation, 3D human pose estimation still remains an open problem. A key challenge is the ill-posed depth ambiguity nature. This paper pres…

cs.CV2017★ 41 cited

Recent Advances in Zero-shot Recognition

Yanwei Fu, Tao Xiang, Yu-Gang Jiang +3

With the recent renaissance of deep convolution neural networks, encouraging breakthroughs have been achieved on the supervised recognition tasks, where each class has sufficient t…

cs.CV2017★ 37 cited

Multi-scale Deep Learning Architectures for Person Re-identification

Xuelin Qian, Yanwei Fu, Yu-Gang Jiang +2

Person Re-identification (re-id) aims to match people across non-overlapping camera views in a public space. It is a challenging problem because many people captured in surveillanc…

cs.CV2017★ 11 cited

A Jointly Learned Deep Architecture for Facial Attribute Analysis and Face Detection in the Wild

Keke He, Yanwei Fu, Xiangyang Xue

Facial attribute analysis in the real world scenario is very challenging mainly because of complex face variations. Existing works of analyzing face attributes are mostly based on…

cs.MM2017★ 6 cited

Modeling Multimodal Clues in a Hybrid Deep Learning Framework for Video Classification

Yu-Gang Jiang, Zuxuan Wu, Jinhui Tang +3

Videos are inherently multimodal. This paper studies the problem of how to fully exploit the abundant multimodal clues for improved video categorization. We introduce a hybrid deep…

cs.CV2017

Vocabulary-informed Extreme Value Learning

Yanwei Fu, HanZe Dong, Yu-feng Ma +2

The novel unseen classes can be formulated as the extreme values of known classes. This inspired the recent works on open-set recognition \cite{Scheirer_2013_TPAMI,Scheirer_2014_TP…