1.2k citations · 1.3k across the 9 of their papers we have counts for
9 papers
Receptive Multi-granularity Representation for Person Re-Identification
Guanshuo Wang, Yufeng Yuan, Jiwei Li +2
A key for person re-identification is achieving consistent local details for discriminative representation across variable environments. Current stripe-based feature learning appro…
Layer Pruning for Accelerating Very Deep Neural Networks
Weiwei Zhang, Changsheng chen, Xuechun Wu +4
In this paper, we propose an adaptive pruning method. This method can cut off the channel and layer adaptively. The proportion of the layer and the channel to be cut is learned ada…
Relation-Aware Pyramid Network (RapNet) for temporal action proposal
Jialin Gao, Zhixiang Shi, Jiani Li +3
In this technical report, we describe our solution to temporal action proposal (task 1) in ActivityNet Challenge 2019. First, we fine-tune a ResNet-50-C3D CNN on ActivityNet v1.3 b…
Pixel-Anchor: A Fast Oriented Scene Text Detector with Combined Networks
Yuan Li, Yuanjie Yu, Zefeng Li +4
Recently, semantic segmentation and general object detection frameworks have been widely adopted by scene text detecting tasks. However, both of them alone have obvious shortcoming…
Self-similarity Grouping: A Simple Unsupervised Cross Domain Adaptation Approach for Person Re-identification
Yang Fu, Yunchao Wei, Guanshuo Wang +3
Domain adaptation in person re-identification (re-ID) has always been a challenging task. In this work, we explore how to harness the natural similar characteristics existing in th…
An improved hybrid CTC-Attention model for speech recognition
Zhe Yuan, Zhuoran Lyu, Jiwei Li +1
Recently, end-to-end speech recognition with a hybrid model consisting of the connectionist temporal classification(CTC) and the attention encoder-decoder achieved state-of-the-art…
A novel pyramidal-FSMN architecture with lattice-free MMI for speech recognition
Xuerui Yang, Jiwei Li, Xi Zhou
Deep Feedforward Sequential Memory Network (DFSMN) has shown superior performance on speech recognition tasks. Based on this work, we propose a novel network architecture which int…
Cascaded CNN-resBiLSTM-CTC: An End-to-End Acoustic Model For Speech Recognition
Xinpei Zhou, Jiwei Li, Xi Zhou
Automatic speech recognition (ASR) tasks are resolved by end-to-end deep learning models, which benefits us by less preparation of raw data, and easier transformation between langu…
Learning Discriminative Features with Multiple Granularities for Person Re-Identification
Guanshuo Wang, Yufeng Yuan, Xiong Chen +2
The combination of global and partial features has been an essential solution to improve discriminative performances in person re-identification (Re-ID) tasks. Previous part-based…