289 citations · 555 across the 3 of their papers we have counts for
3 papers
cs.CV2016★ 289 cited
Temporal Segment Networks: Towards Good Practices for Deep Action Recognition
Limin Wang, Yuanjun Xiong, Zhe Wang +4
Deep convolutional networks have achieved great success for visual recognition in still images. However, for action recognition in videos, the advantage over traditional methods is…
cs.CV2016★ 132 cited
CUHK & ETHZ & SIAT Submission to ActivityNet Challenge 2016
Yuanjun Xiong, Limin Wang, Zhe Wang +7
This paper presents the method that underlies our submission to the untrimmed video classification task of ActivityNet Challenge 2016. We follow the basic pipeline of temporal segm…
cs.CV2014★ 134 cited
DeepID-Net: multi-stage and deformable deep convolutional neural networks for object detection
Wanli Ouyang, Ping Luo, Xingyu Zeng +12
In this paper, we propose multi-stage and deformable deep convolutional neural networks for object detection. This new deep learning object detection diagram has innovations in mul…