most citedEnhancing Label-efficient Medical Image Segmentation with Text-guided Diffusion Models

1 citations · 1 across the 4 of their papers we have counts for

collaborators

7 papers

cs.CV2025

PhysRig: Differentiable Physics-Based Skinning and Rigging Framework for Realistic Articulated Object Modeling

Hao Zhang, Haolan Xu, Chun Feng +2

Skinning and rigging are fundamental components in animation, articulated object reconstruction, motion transfer, and 4D generation. Existing approaches predominantly rely on Linea…

eess.IV2025

Spatio-Temporal Representation Decoupling and Enhancement for Federated Instrument Segmentation in Surgical Videos

Zheng Fang, Xiaoming Qi, Chun-Mei Feng +3

Surgical instrument segmentation under Federated Learning (FL) is a promising direction, which enables multiple surgical sites to collaboratively train the model without centralizi…

cs.CV2025

Neural Catalog: Scaling Species Recognition with Catalog of Life-Augmented Generation

Faizan Farooq Khan, Jun Chen, Youssef Mohamed +2

Open-vocabulary species recognition is a major challenge in computer vision, particularly in ornithology, where new taxa are continually discovered. While benchmarks like CUB-200-2…

cs.CV2025

WikiAutoGen: Towards Multi-Modal Wikipedia-Style Article Generation

Zhongyu Yang, Jun Chen, Dannong Xu +5

Knowledge discovery and collection are intelligence-intensive tasks that traditionally require significant human effort to ensure high-quality outputs. Recent research has explored…

cs.CV2024

Document Haystacks: Vision-Language Reasoning Over Piles of 1000+ Documents

Jun Chen, Dannong Xu, Junjie Fei +2

Large multimodal models (LMMs) have achieved impressive progress in vision-language understanding, yet they face limitations in real-world applications requiring complex reasoning…

eess.IV20241 cited

Enhancing Label-efficient Medical Image Segmentation with Text-guided Diffusion Models

Chun-Mei Feng

Aside from offering state-of-the-art performance in medical image generation, denoising diffusion probabilistic models (DPM) can also serve as a representation learner to capture s…