5 citations · 11 across the 25 of their papers we have counts for
8 papers · 1 filter
ORID: Organ-Regional Information Driven Framework for Radiology Report Generation
Tiancheng Gu, Kaicheng Yang, Xiang An +3
The objective of Radiology Report Generation (RRG) is to automatically generate coherent textual analyses of diseases based on radiological images, thereby alleviating the workload…
ViCToR: Improving Visual Comprehension via Token Reconstruction for Pretraining LMMs
Yin Xie, Kaicheng Yang, Peirou Liang +7
Large Multimodal Models (LMMs) often face a modality representation gap during pretraining: while language embeddings remain stable, visual representations are highly sensitive to…
CLIP-CID: Efficient CLIP Distillation via Cluster-Instance Discrimination
Kaicheng Yang, Tiancheng Gu, Xiang An +5
Contrastive Language-Image Pre-training (CLIP) has achieved excellent performance over a wide range of tasks. However, the effectiveness of CLIP heavily relies on a substantial cor…
Multi-label Cluster Discrimination for Visual Representation Learning
Xiang An, Kaicheng Yang, Xiangzi Dai +2
Contrastive Language Image Pre-training (CLIP) has recently demonstrated success across various tasks due to superior feature representation empowered by image-text contrastive lea…
High-Fidelity Facial Albedo Estimation via Texture Quantization
Zimin Ran, Xingyu Ren, Xiang An +6
Recent 3D face reconstruction methods have made significant progress in shape estimation, but high-fidelity facial albedo reconstruction remains challenging. Existing methods depen…
RWKV-CLIP: A Robust Vision-Language Representation Learner
Tiancheng Gu, Kaicheng Yang, Xiang An +4
Contrastive Language-Image Pre-training (CLIP) has significantly improved performance in various vision-language tasks by expanding the dataset with image-text pairs obtained from…
1st Place Solution to the 1st SkatingVerse Challenge
Tao Sun, Yuanzi Fu, Kaicheng Yang +2
This paper presents the winning solution for the 1st SkatingVerse Challenge. We propose a method that involves several steps. To begin, we leverage the DINO framework to extract th…
LaPA: Latent Prompt Assist Model For Medical Visual Question Answering
Tiancheng Gu, Kaicheng Yang, Dongnan Liu +1
Medical visual question answering (Med-VQA) aims to automate the prediction of correct answers for medical images and questions, thereby assisting physicians in reducing repetitive…