1.6k citations · 4.8k across the 90 of their papers we have counts for
12 papers · 1 filter
Enhance Visual Recognition under Adverse Conditions via Deep Networks
Ding Liu, Bowen Cheng, Zhangyang Wang +2
Visual recognition under adverse conditions is a very important and challenging problem of high practical value, due to the ubiquitous existence of quality distortions during image…
Improving Object Detection from Scratch via Gated Feature Reuse
Zhiqiang Shen, Honghui Shi, Jiahui Yu +7
In this paper, we present a simple and parameter-efficient drop-in module for one-stage object detectors like SSD when learning from scratch (i.e., without pre-trained models). We…
Dilated Recurrent Neural Networks
Shiyu Chang, Yang Zhang, Wei Han +7
Learning with recurrent neural networks (RNNs) on long sequences is a notoriously difficult task. There are three major challenges: 1) complex dependencies, 2) vanishing and explod…
Robust Emotion Recognition from Low Quality and Low Bit Rate Video: A Deep Learning Approach
Bowen Cheng, Zhangyang Wang, Zhaobin Zhang +5
Emotion recognition from facial expressions is tremendously useful, especially when coupled with smart devices and wireless multimedia applications. However, the inadequate network…
Discriminative Similarity for Clustering and Semi-Supervised Learning
Yingzhen Yang, Feng Liang, Nebojsa Jojic +3
Similarity-based clustering and semi-supervised learning methods separate the data into clusters or classes according to the pairwise similarity between the data, and the pairwise…
On the Suboptimality of Proximal Gradient Descent for Sparse Approximation
Yingzhen Yang, Jiashi Feng, Nebojsa Jojic +2
We study the proximal gradient descent (PGD) method for sparse approximation problem as well as its accelerated optimization with randomized algorithms in this paper. We…