3 papers
cs.CV2024
Diffusion Product Quantization
Jie Shao, Hanxiao Zhang, Jianxin Wu
In this work, we explore the quantization of diffusion models in extreme compression regimes to reduce model size while maintaining performance. We begin by investigating classical…
cs.CV2024
Dense Vision Transformer Compression with Few Samples
Hanxiao Zhang, Yifan Zhou, Guo-Hua Wang +1
Few-shot model compression aims to compress a large model into a more compact one with only a tiny training set (even without labels). Block-level pruning has recently emerged as a…
cs.CV2024
DiffuLT: How to Make Diffusion Model Useful for Long-tail Recognition
Jie Shao, Ke Zhu, Hanxiao Zhang +1
This paper proposes a new pipeline for long-tail (LT) recognition. Instead of re-weighting or re-sampling, we utilize the long-tailed dataset itself to generate a balanced proxy th…