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20222026
most citedAIM 2024 Challenge on Video Super-Resolution Quality Assessment: Methods and Results

7 citations · 7 across the 13 of their papers we have counts for

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8 papers · 1 filter

cs.CV2026

NTIRE 2026 Challenge on Video Saliency Prediction: Methods and Results

Andrey Moskalenko, Alexey Bryncev, Ivan Kosmynin +40

This paper presents an overview of the NTIRE 2026 Challenge on Video Saliency Prediction. The goal of the challenge participants was to develop automatic saliency map prediction me…

cs.CV2026

LoViF 2026 Challenge on Human-oriented Semantic Image Quality Assessment: Methods and Results

Xin Li, Daoli Xu, Wei Luo +27

This paper reviews the LoViF 2026 Challenge on Human-oriented Semantic Image Quality Assessment. This challenge aims to raise a new direction, i.e., how to evaluate the loss of sem…

cs.CV2026

A Reasoning-Enabled Vision-Language Foundation Model for Chest X-ray Interpretation

Yabin Zhang, Chong Wang, Yunhe Gao +19

Chest X-rays (CXRs) are among the most frequently performed imaging examinations worldwide, yet rising imaging volumes increase radiologist workload and the risk of diagnostic erro…

cs.CV2026

Activation Matters: Test-time Activated Negative Labels for OOD Detection with Vision-Language Models

Yabin Zhang, Maya Varma, Yunhe Gao +4

Out-of-distribution (OOD) detection aims to identify samples that deviate from in-distribution (ID). One popular pipeline addresses this by introducing negative labels distant from…

cs.CV2026

ME-IQA: Memory-Enhanced Image Quality Assessment via Re-Ranking

Kanglong Fan, Tianhe Wu, Wen Wen +6

Reasoning-induced vision-language models (VLMs) advance image quality assessment (IQA) with textual reasoning, yet their scalar scores often lack sensitivity and collapse to a few…

cs.CV2026

A data- and compute-efficient chest X-ray foundation model beyond aggressive scaling

Chong Wang, Yabin Zhang, Yunhe Gao +9

Foundation models for medical imaging are typically pretrained on increasingly large datasets, following a "scale-at-all-costs" paradigm. However, this strategy faces two critical…

cs.CV2026

Unpaired Image-to-Image Translation via a Self-Supervised Semantic Bridge

Jiaming Liu, Felix Petersen, Yunhe Gao +6

Adversarial diffusion and diffusion-inversion methods have advanced unpaired image-to-image translation, but each faces key limitations. Adversarial approaches require target-domai…

cs.LG2026

Gradient-Stable Attention Heads Signal LLM Correctness

Sophie Ostmeier, Brian Axelrod, Maya Varma +6

Large language models (LLMs) often generate plausible yet incorrect answers, posing risks in safety-critical settings such as medicine. Human evaluation is expensive, and LLM-as-ju…