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cs.CV2026

Low Light Image Enhancement Challenge at NTIRE 2026

George Ciubotariu, Sharif S M A, Abdur Rehman +90

This paper presents a comprehensive review of the NTIRE 2026 Low Light Image Enhancement Challenge, highlighting the proposed solutions and final results. The objective of this cha…

cs.CV2026

NTIRE 2026 The Second Challenge on Day and Night Raindrop Removal for Dual-Focused Images: Methods and Results

Xin Li, Yeying Jin, Suhang Yao +95

This paper presents an overview of the NTIRE 2026 Second Challenge on Day and Night Raindrop Removal for Dual-Focused Images. Building upon the success of the first edition, this c…

cs.CV2026

Bias-constrained multimodal intelligence for equitable and reliable clinical AI

Cheng Li, Weijian Huang, Jiarun Liu +6

The integration of medical imaging and clinical text has enabled the emergence of generalist artificial intelligence (AI) systems for healthcare. However, pervasive biases, such as…

cs.CV2025

A multi-modal vision-language model for generalizable annotation-free pathology localization

Hao Yang, Hong-Yu Zhou, Jiarun Liu +12

Existing deep learning models for defining pathology from clinical imaging data rely on expert annotations and lack generalization capabilities in open clinical environments. Here,…

cs.CV2025

BioVFM-21M: Benchmarking and Scaling Self-Supervised Vision Foundation Models for Biomedical Image Analysis

Jiarun Liu, Hong-Yu Zhou, Weijian Huang +5

Scaling up model and data size have demonstrated impressive performance improvement over a wide range of tasks. Despite extensive studies on scaling behaviors for general-purpose t…

cs.CV2024

Enhancing the vision-language foundation model with key semantic knowledge-emphasized report refinement

Weijian Huang, Cheng Li, Hao Yang +4

Recently, vision-language representation learning has made remarkable advancements in building up medical foundation models, holding immense potential for transforming the landscap…