18 citations · 70 across the 16 of their papers we have counts for
14 papers · 1 filter
Vision-Language Dataset Distillation
Xindi Wu, Byron Zhang, Zhiwei Deng +1
Dataset distillation methods reduce large-scale datasets to smaller sets of synthetic data, preserving sufficient information to quickly train a new model from scratch. However, pr…
Revisiting the Parameter Efficiency of Adapters from the Perspective of Precision Redundancy
Shibo Jie, Haoqing Wang, Zhi-Hong Deng
Current state-of-the-art results in computer vision depend in part on fine-tuning large pre-trained vision models. However, with the exponential growth of model sizes, the conventi…
Masked Image Modeling with Local Multi-Scale Reconstruction
Haoqing Wang, Yehui Tang, Yunhe Wang +3
Masked Image Modeling (MIM) achieves outstanding success in self-supervised representation learning. Unfortunately, MIM models typically have huge computational burden and slow lea…
Boundary Guided Learning-Free Semantic Control with Diffusion Models
Ye Zhu, Yu Wu, Zhiwei Deng +2
Applying pre-trained generative denoising diffusion models (DDMs) for downstream tasks such as image semantic editing usually requires either fine-tuning DDMs or learning auxiliary…
Global-to-local Expression-aware Embeddings for Facial Action Unit Detection
Rudong An, Wei Zhang, Hao Zeng +3
Expressions and facial action units (AUs) are two levels of facial behavior descriptors. Expression auxiliary information has been widely used to improve the AU detection performan…
Facial Action Units Detection Aided by Global-Local Expression Embedding
Zhipeng Hu, Wei Zhang, Lincheng Li +4
Since Facial Action Unit (AU) annotations require domain expertise, common AU datasets only contain a limited number of subjects. As a result, a crucial challenge for AU detection…