activity
20152023
most citedTowards Good Practices for Very Deep Two-Stream ConvNets

385 citations · 1.5k across the 34 of their papers we have counts for

collaborators
Showing 2017Show all

5 papers · 1 filter

cs.CV2017313 cited

WebVision Database: Visual Learning and Understanding from Web Data

Wen Li, Limin Wang, Wei Li +2

In this paper, we present a study on learning visual recognition models from large scale noisy web data. We build a new database called WebVision, which contains more than mi…

cs.CV201714 cited

WebVision Challenge: Visual Learning and Understanding With Web Data

Wen Li, Limin Wang, Wei Li +5

We present the 2017 WebVision Challenge, a public image recognition challenge designed for deep learning based on web images without instance-level human annotation. Following the…

cs.CV2017

Temporal Segment Networks for Action Recognition in Videos

Limin Wang, Yuanjun Xiong, Zhe Wang +4

Deep convolutional networks have achieved great success for image recognition. However, for action recognition in videos, their advantage over traditional methods is not so evident…

cs.CV201713 cited

Thin-Slicing Network: A Deep Structured Model for Pose Estimation in Videos

Jie Song, Limin Wang, Luc Van Gool +1

Deep ConvNets have been shown to be effective for the task of human pose estimation from single images. However, several challenging issues arise in the video-based case such as se…

cs.CV2017132 cited

A Pursuit of Temporal Accuracy in General Activity Detection

Yuanjun Xiong, Yue Zhao, Limin Wang +2

Detecting activities in untrimmed videos is an important but challenging task. The performance of existing methods remains unsatisfactory, e.g., they often meet difficulties in loc…