activity
20142019
most citedR2CNN: Rotational Region CNN for Orientation Robust Scene Text Detection

490 citations · 769 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV20193 cited

Deformable Tube Network for Action Detection in Videos

Wei Li, Zehuan Yuan, Dashan Guo +3

We address the problem of spatio-temporal action detection in videos. Existing methods commonly either ignore temporal context in action recognition and localization, or lack the m…

cs.CV201736 cited

Attribute Recognition by Joint Recurrent Learning of Context and Correlation

Jingya Wang, Xiatian Zhu, Shaogang Gong +1

Recognising semantic pedestrian attributes in surveillance images is a challenging task for computer vision, particularly when the imaging quality is poor with complex background c…

cs.CV201794 cited

SAR Target Recognition Using the Multi-aspect-aware Bidirectional LSTM Recurrent Neural Networks

Fan Zhang, Chen Hu, Qiang Yin +3

The outstanding pattern recognition performance of deep learning brings new vitality to the synthetic aperture radar (SAR) automatic target recognition (ATR). However, there is a l…

cs.CV2017490 cited

R2CNN: Rotational Region CNN for Orientation Robust Scene Text Detection

Yingying Jiang, Xiangyu Zhu, Xiaobing Wang +5

In this paper, we propose a novel method called Rotational Region CNN (R2CNN) for detecting arbitrary-oriented texts in natural scene images. The framework is based on Faster R-CNN…

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.CV2016132 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…