LAMM: Label Alignment for Multi-Modal Prompt Learning

1 code implementation • 13 Dec 2023 • Jingsheng Gao, Jiacheng Ruan, Suncheng Xiang, Zefang Yu, Ke Ji, Mingye Xie, Ting Liu, Yuzhuo Fu

We conduct experiments on 11 downstream vision datasets and demonstrate that our method significantly improves the performance of existing multi-modal prompt learning models in few-shot scenarios, exhibiting an average accuracy improvement of 2. 31(\%) compared to the state-of-the-art methods on 16 shots.

Continual Learning

GIST: Improving Parameter Efficient Fine Tuning via Knowledge Interaction

1 code implementation • 12 Dec 2023 • Jiacheng Ruan, Jingsheng Gao, Mingye Xie, Suncheng Xiang, Zefang Yu, Ting Liu, Yuzhuo Fu

2) They neglect the interaction between the intrinsic task-agnostic knowledge of pre-trained models and the task-specific knowledge in downstream tasks.

Colo-SCRL: Self-Supervised Contrastive Representation Learning for Colonoscopic Video Retrieval

no code implementations • 28 Mar 2023 • Qingzhong Chen, Shilun Cai, Crystal Cai, Zefang Yu, Dahong Qian, Suncheng Xiang

To seek a solution to this problem, we construct a large-scale colonoscopic dataset named Colo-Pair for medical practice.

Action Recognition Contrastive Learning +4

Deep Multimodal Fusion for Generalizable Person Re-identification

1 code implementation • 2 Nov 2022 • Suncheng Xiang, Hao Chen, Wei Ran, Zefang Yu, Ting Liu, Dahong Qian, Yuzhuo Fu

Person re-identification plays a significant role in realistic scenarios due to its various applications in public security and video surveillance.

Domain Generalization Generalizable Person Re-identification +2