57 citations · 169 across the 26 of their papers we have counts for
32 papers
TraDiffusion: Trajectory-Based Training-Free Image Generation
Mingrui Wu, Oucheng Huang, Jiayi Ji +6
In this work, we propose a training-free, trajectory-based controllable T2I approach, termed TraDiffusion. This novel method allows users to effortlessly guide image generation via…
STAR Loss: Reducing Semantic Ambiguity in Facial Landmark Detection
Zhenglin Zhou, Huaxia Li, Hong Liu +3
Recently, deep learning-based facial landmark detection has achieved significant improvement. However, the semantic ambiguity problem degrades detection performance. Specifically,…
DiffRate : Differentiable Compression Rate for Efficient Vision Transformers
Mengzhao Chen, Wenqi Shao, Peng Xu +6
Token compression aims to speed up large-scale vision transformers (e.g. ViTs) by pruning (dropping) or merging tokens. It is an important but challenging task. Although recent adv…
CamoDiffusion: Camouflaged Object Detection via Conditional Diffusion Models
Zhongxi Chen, Ke Sun, Xianming Lin +1
Camouflaged Object Detection (COD) is a challenging task in computer vision due to the high similarity between camouflaged objects and their surroundings. Existing COD methods prim…
RefBERT: A Two-Stage Pre-trained Framework for Automatic Rename Refactoring
Hao Liu, Yanlin Wang, Zhao Wei +4
Refactoring is an indispensable practice of improving the quality and maintainability of source code in software evolution. Rename refactoring is the most frequently performed refa…
Distribution-Flexible Subset Quantization for Post-Quantizing Super-Resolution Networks
Yunshan Zhong, Mingbao Lin, Jingjing Xie +3
This paper introduces Distribution-Flexible Subset Quantization (DFSQ), a post-training quantization method for super-resolution networks. Our motivation for developing DFSQ is bas…