10 citations · 14 across the 2 of their papers we have counts for
5 papers · 1 filter
SMAUG: Sparse Masked Autoencoder for Efficient Video-Language Pre-training
Yuanze Lin, Chen Wei, Huiyu Wang +2
Video-language pre-training is crucial for learning powerful multi-modal representation. However, it typically requires a massive amount of computation. In this paper, we develop S…
CReST: A Class-Rebalancing Self-Training Framework for Imbalanced Semi-Supervised Learning
Chen Wei, Kihyuk Sohn, Clayton Mellina +2
Semi-supervised learning on class-imbalanced data, although a realistic problem, has been under studied. While existing semi-supervised learning (SSL) methods are known to perform…
CO2: Consistent Contrast for Unsupervised Visual Representation Learning
Chen Wei, Huiyu Wang, Wei Shen +1
Contrastive learning has been adopted as a core method for unsupervised visual representation learning. Without human annotation, the common practice is to perform an instance disc…
Iterative Reorganization with Weak Spatial Constraints: Solving Arbitrary Jigsaw Puzzles for Unsupervised Representation Learning
Chen Wei, Lingxi Xie, Xutong Ren +5
Learning visual features from unlabeled image data is an important yet challenging task, which is often achieved by training a model on some annotation-free information. We conside…
Deep Retinex Decomposition for Low-Light Enhancement
Chen Wei, Wenjing Wang, Wenhan Yang +1
Retinex model is an effective tool for low-light image enhancement. It assumes that observed images can be decomposed into the reflectance and illumination. Most existing Retinex-b…