49 citations · 63 across the 9 of their papers we have counts for
4 papers · 1 filter
Dataset Condensation via Generative Model
David Junhao Zhang, Heng Wang, Chuhui Xue +4
Dataset condensation aims to condense a large dataset with a lot of training samples into a small set. Previous methods usually condense the dataset into the pixels format. However…
Free-ATM: Exploring Unsupervised Learning on Diffusion-Generated Images with Free Attention Masks
David Junhao Zhang, Mutian Xu, Chuhui Xue +4
Despite the rapid advancement of unsupervised learning in visual representation, it requires training on large-scale datasets that demand costly data collection, and pose additiona…
Too Large; Data Reduction for Vision-Language Pre-Training
Alex Jinpeng Wang, Kevin Qinghong Lin, David Junhao Zhang +2
This paper examines the problems of severe image-text misalignment and high redundancy in the widely-used large-scale Vision-Language Pre-Training (VLP) datasets. To address these…
Making Vision Transformers Efficient from A Token Sparsification View
Shuning Chang, Pichao Wang, Ming Lin +4
The quadratic computational complexity to the number of tokens limits the practical applications of Vision Transformers (ViTs). Several works propose to prune redundant tokens to a…