864 citations · 1.9k across the 57 of their papers we have counts for
8 papers · 1 filter
Faster First-Order Methods for Stochastic Non-Convex Optimization on Riemannian Manifolds
Pan Zhou, Xiao-Tong Yuan, Jiashi Feng
SPIDER (Stochastic Path Integrated Differential EstimatoR) is an efficient gradient estimation technique developed for non-convex stochastic optimization. Although having been show…
Bayesian Cycle-Consistent Generative Adversarial Networks via Marginalizing Latent Sampling
Haoran You, Yu Cheng, Tianheng Cheng +2
Recent techniques built on Generative Adversarial Networks (GANs), such as Cycle-Consistent GANs, are able to learn mappings among different domains built from unpaired datasets, t…
Modality Attention for End-to-End Audio-visual Speech Recognition
Pan Zhou, Wenwen Yang, Wei Chen +2
Audio-visual speech recognition (AVSR) system is thought to be one of the most promising solutions for robust speech recognition, especially in noisy environment. In this paper, we…
An Online Attention-based Model for Speech Recognition
Ruchao Fan, Pan Zhou, Wei Chen +2
Attention-based end-to-end models such as Listen, Attend and Spell (LAS), simplify the whole pipeline of traditional automatic speech recognition (ASR) systems and become popular i…
Exploring RNN-Transducer for Chinese Speech Recognition
Senmao Wang, Pan Zhou, Wei Chen +2
End-to-end approaches have drawn much attention recently for significantly simplifying the construction of an automatic speech recognition (ASR) system. RNN transducer (RNN-T) is o…
Spatial-Temporal Synergic Residual Learning for Video Person Re-Identification
Xinxing Su, Yingtian Zou, Yu Cheng +3
We tackle the problem of person re-identification in video setting in this paper, which has been viewed as a crucial task in many applications. Meanwhile, it is very challenging si…
Understanding Generalization and Optimization Performance of Deep CNNs
Pan Zhou, Jiashi Feng
This work aims to provide understandings on the remarkable success of deep convolutional neural networks (CNNs) by theoretically analyzing their generalization performance and esta…
Pedestrian-Synthesis-GAN: Generating Pedestrian Data in Real Scene and Beyond
Xi Ouyang, Yu Cheng, Yifan Jiang +2
State-of-the-art pedestrian detection models have achieved great success in many benchmarks. However, these models require lots of annotation information and the labeling process u…