289 citations · 593 across the 14 of their papers we have counts for
Showing 2016Show all
3 papers · 1 filter
cs.CV2016★ 1 cited
Deep Markov Random Field for Image Modeling
Zhirong Wu, Dahua Lin, Xiaoou Tang
Markov Random Fields (MRFs), a formulation widely used in generative image modeling, have long been plagued by the lack of expressive power. This issue is primarily due to the fact…
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…