2 citations · 5 across the 4 of their papers we have counts for
4 papers
DVF: Advancing Robust and Accurate Fine-Grained Image Retrieval with Retrieval Guidelines
Xin Jiang, Hao Tang, Rui Yan +2
Fine-grained image retrieval (FGIR) is to learn visual representations that distinguish visually similar objects while maintaining generalization. Existing methods propose to gener…
Retrieval-based Knowledge Transfer: An Effective Approach for Extreme Large Language Model Compression
Jiduan Liu, Jiahao Liu, Qifan Wang +5
Large-scale pre-trained language models (LLMs) have demonstrated exceptional performance in various natural language processing (NLP) tasks. However, the massive size of these mode…
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…
MNet: Multi-view Encoding, Matching, and Fusion for Few-shot Fine-grained Action Recognition
Hao Tang, Jun Liu, Shuanglin Yan +3
Due to the scarcity of manually annotated data required for fine-grained video understanding, few-shot fine-grained (FS-FG) action recognition has gained significant attention, wit…