31 citations · 136 across the 28 of their papers we have counts for
6 papers · 1 filter
Adversarial Memory Networks for Action Prediction
Zhiqiang Tao, Yue Bai, Handong Zhao +3
Action prediction aims to infer the forthcoming human action with partially-observed videos, which is a challenging task due to the limited information underlying early observation…
SLAP: Self-supervised Anomaly Detection with Adversarial Perturbation
Yizhou Wang, Can Qin, Rongzhe Wei +3
Anomaly detection is a fundamental yet challenging problem in machine learning due to the lack of label information. In this work, we propose a novel and powerful framework, dubbed…
Sign Language Recognition via Skeleton-Aware Multi-Model Ensemble
Songyao Jiang, Bin Sun, Lichen Wang +3
Sign language is commonly used by deaf or mute people to communicate but requires extensive effort to master. It is usually performed with the fast yet delicate movement of hand ge…
Dynamical Isometry: The Missing Ingredient for Neural Network Pruning
Huan Wang, Can Qin, Yue Bai +1
Several recent works [40, 24] observed an interesting phenomenon in neural network pruning: A larger finetuning learning rate can improve the final performance significantly. Unfor…
Skeleton Aware Multi-modal Sign Language Recognition
Songyao Jiang, Bin Sun, Lichen Wang +3
Sign language is commonly used by deaf or speech impaired people to communicate but requires significant effort to master. Sign Language Recognition (SLR) aims to bridge the gap be…
Recent Advances on Neural Network Pruning at Initialization
Huan Wang, Can Qin, Yue Bai +2
Neural network pruning typically removes connections or neurons from a pretrained converged model; while a new pruning paradigm, pruning at initialization (PaI), attempts to prune…