133 citations · 379 across the 7 of their papers we have counts for
7 papers
iCAR: Bridging Image Classification and Image-text Alignment for Visual Recognition
Yixuan Wei, Yue Cao, Zheng Zhang +4
Image classification, which classifies images by pre-defined categories, has been the dominant approach to visual representation learning over the last decade. Visual learning thro…
SimMIM: A Simple Framework for Masked Image Modeling
Zhenda Xie, Zheng Zhang, Yue Cao +5
This paper presents SimMIM, a simple framework for masked image modeling. We simplify recently proposed related approaches without special designs such as block-wise masking and to…
Swin Transformer V2: Scaling Up Capacity and Resolution
Ze Liu, Han Hu, Yutong Lin +9
Large-scale NLP models have been shown to significantly improve the performance on language tasks with no signs of saturation. They also demonstrate amazing few-shot capabilities l…
Self-Supervised Learning with Swin Transformers
Zhenda Xie, Yutong Lin, Zhuliang Yao +4
We are witnessing a modeling shift from CNN to Transformers in computer vision. In this work, we present a self-supervised learning approach called MoBY, with Vision Transformers a…
Disentangled Non-Local Neural Networks
Minghao Yin, Zhuliang Yao, Yue Cao +4
The non-local block is a popular module for strengthening the context modeling ability of a regular convolutional neural network. This paper first studies the non-local block in de…
Cross-Iteration Batch Normalization
Zhuliang Yao, Yue Cao, Shuxin Zheng +2
A well-known issue of Batch Normalization is its significantly reduced effectiveness in the case of small mini-batch sizes. When a mini-batch contains few examples, the statistics…
Balanced Sparsity for Efficient DNN Inference on GPU
Zhuliang Yao, Shijie Cao, Wencong Xiao +2
In trained deep neural networks, unstructured pruning can reduce redundant weights to lower storage cost. However, it requires the customization of hardwares to speed up practical…