16 citations · 24 across the 6 of their papers we have counts for
6 papers
CoVFT: Context-aware Visual Fine-tuning for Multimodal Large Language Models
Nan Zhou, Huiqun Wang, Yaoyan Zheng +1
Multimodal large language models (MLLMs) achieve remarkable progress in cross-modal perception and reasoning, yet a fundamental question remains unresolved: should the vision encod…
A multimodal vision foundation model for generalizable knee pathology
Kang Yu, Dingyu Wang, Zimu Yuan +8
Musculoskeletal disorders represent a leading cause of global disability, creating an urgent demand for precise interpretation of medical imaging. Current artificial intelligence (…
Implicit Modeling for Transferability Estimation of Vision Foundation Models
Yaoyan Zheng, Huiqun Wang, Nan Zhou +1
Transferability estimation identifies the best pre-trained models for downstream tasks without incurring the high computational cost of full fine-tuning. This capability facilitate…
Crowd-SAM: SAM as a Smart Annotator for Object Detection in Crowded Scenes
Zhi Cai, Yingjie Gao, Yaoyan Zheng +2
In computer vision, object detection is an important task that finds its application in many scenarios. However, obtaining extensive labels can be challenging, especially in crowde…
Deep Common Feature Mining for Efficient Video Semantic Segmentation
Yaoyan Zheng, Hongyu Yang, Di Huang
Recent advancements in video semantic segmentation have made substantial progress by exploiting temporal correlations. Nevertheless, persistent challenges, including redundant comp…
Checkerboard Context Model for Efficient Learned Image Compression
Dailan He, Yaoyan Zheng, Baocheng Sun +2
For learned image compression, the autoregressive context model is proved effective in improving the rate-distortion (RD) performance. Because it helps remove spatial redundancies…