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cs.CV2026

Bridging Information Asymmetry: A Hierarchical Framework for Deterministic Blind Face Restoration

Zhengjian Yao, Jiakui Hu, Kaiwen Li +5

Blind face restoration remains a persistent challenge due to the inherent ill-posedness of reconstructing holistic structures from severely constrained observations. Current genera…

cs.CV2025

Inter- and Intra-image Refinement for Few Shot Segmentation

Ourui Fu, Hangzhou He, Kaiwen Li +5

Deep neural networks for semantic segmentation rely on large-scale annotated datasets, leading to an annotation bottleneck that motivates few shot semantic segmentation (FSS) which…

cs.CV2025

AdaTok: Adaptive Token Compression with Object-Aware Representations for Efficient Multimodal LLMs

Xinliang Zhang, Lei Zhu, Hangzhou He +5

Multimodal Large Language Models (MLLMs) have demonstrated substantial value in unified text-image understanding and reasoning, primarily by converting images into sequences of pat…

cs.CV2025

Chat-CBM: Towards Interactive Concept Bottleneck Models with Frozen Large Language Models

Hangzhou He, Lei Zhu, Kaiwen Li +5

Concept Bottleneck Models (CBMs) provide inherent interpretability by first predicting a set of human-understandable concepts and then mapping them to labels through a simple class…

cs.CV2025

Enhancing Image Restoration Transformer via Adaptive Translation Equivariance

JiaKui Hu, Zhengjian Yao, Lujia Jin +2

Translation equivariance is a fundamental inductive bias in image restoration, ensuring that translated inputs produce translated outputs. Attention mechanisms in modern restoratio…

cs.CV2025

Training-free Test-time Improvement for Explainable Medical Image Classification

Hangzhou He, Jiachen Tang, Lei Zhu +2

Deep learning-based medical image classification techniques are rapidly advancing in medical image analysis, making it crucial to develop accurate and trustworthy models that can b…