3 citations · 4 across the 14 of their papers we have counts for
16 papers
UnfoldCRF: Structured Mask Refinement with Image-Conditioned Latent Regions
Chunming He, Rihan Zhang, Lei Xu +5
Learned mask refiners improve segmentation accuracy, but it is hard to tell how much of the improvement comes from explicit structure rather than from extra capacity, and whether i…
Tool-IQA: Augmenting Image Quality Assessment with Simple Tools
Guanyi Qin, Junjie Zhang, Chunming He +4
Vision-Language Models (VLMs) have been increasingly adopted for Image Quality Assessment (IQA). However, current methods typically employ a static one-shot scoring paradigm, despi…
NTIRE 2026 The 3rd Restore Any Image Model (RAIM) Challenge: Professional Image Quality Assessment (Track 1)
Guanyi Qin, Jie Liang, Bingbing Zhang +50
In this paper, we present an overview of the NTIRE 2026 challenge on the 3rd Restore Any Image Model in the Wild, specifically focusing on Track 1: Professional Image Quality Asses…
NTIRE 2026 The 3rd Restore Any Image Model (RAIM) Challenge: AI Flash Portrait (Track 3)
Ya-nan Guan, Shaonan Zhang, Hang Guo +55
In this paper, we present a comprehensive overview of the NTIRE 2026 3rd Restore Any Image Model (RAIM) challenge, with a specific focus on Track 3: AI Flash Portrait. Despite sign…
NTIRE 2026 The 3rd Restore Any Image Model (RAIM) Challenge: Multi-Exposure Image Fusion in Dynamic Scenes (Track 2)
Lishen Qu, Yao Liu, Jie Liang +32
This paper presents NTIRE 2026, the 3rd Restore Any Image Model (RAIM) challenge on multi-exposure image fusion in dynamic scenes. We introduce a benchmark that targets a practical…
UniSurgSAM: A Unified Promptable Model for Reliable Surgical Video Segmentation
Haofeng Liu, Ziyue Wang, Alex Y. W. Kong +6
Surgical video segmentation is fundamental to computer-assisted surgery. In practice, surgeons need to dynamically specify targets throughout extended procedures, using heterogeneo…
Beyond Ground-Truth: Leveraging Image Quality Priors for Real-World Image Restoration
Fengyang Xiao, Peng Hu, Lei Xu +7
Real-world image restoration aims to restore high-quality (HQ) images from degraded low-quality (LQ) inputs captured under uncontrolled conditions. Existing methods typically depen…
QualiTeacher: Quality-Conditioned Pseudo-Labeling for Real-World Image Restoration
Fengyang Xiao, Jingjia Feng, Peng Hu +6
Real-world image restoration (RWIR) is a highly challenging task due to the absence of clean ground-truth images. Many recent methods resort to pseudo-label (PL) supervision, often…
SurGo-R1: Benchmarking and Modeling Contextual Reasoning for Operative Zone in Surgical Video
Guanyi Qin, Xiaozhen Wang, Zhu Zhuo +7
Minimally invasive surgery has dramatically improved patient operative outcomes, yet identifying safe operative zones remains challenging in critical phases, requiring surgeons to…
DR.Experts: Differential Refinement of Distortion-Aware Experts for Blind Image Quality Assessment
Bohan Fu, Guanyi Qin, Fazhan Zhang +3
Blind Image Quality Assessment, aiming to replicate human perception of visual quality without reference, plays a key role in vision tasks, yet existing models often fail to effect…
SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking
Haofeng Liu, Ziyue Wang, Sudhanshu Mishra +8
Surgical scene understanding demands temporally consistent tracking of instruments and tissues. For clinical use, such tracking should generalize to new centers and procedure types…
Structure Matters: Revisiting Boundary Refinement in Video Object Segmentation
Guanyi Qin, Ziyue Wang, Daiyun Shen +5
Given an object mask, Semi-supervised Video Object Segmentation (SVOS) technique aims to track and segment the object across video frames, serving as a fundamental task in computer…
ReSurgSAM2: Referring Segment Anything in Surgical Video via Credible Long-term Tracking
Haofeng Liu, Mingqi Gao, Xuxiao Luo +4
Surgical scene segmentation is critical in computer-assisted surgery and is vital for enhancing surgical quality and patient outcomes. Recently, referring surgical segmentation is…
Gamma: Toward Generic Image Assessment with Mixture of Assessment Experts
Hantao Zhou, Rui Yang, Longxiang Tang +3
Image assessment aims to evaluate the quality and aesthetics of images and has been applied across various scenarios, such as natural and AIGC scenes. Existing methods mostly addre…
UniQA: Unified Vision-Language Pre-training for Image Quality and Aesthetic Assessment
Hantao Zhou, Longxiang Tang, Rui Yang +6
Image Quality Assessment (IQA) and Image Aesthetic Assessment (IAA) aim to simulate human subjective perception of image visual quality and aesthetic appeal. Despite distinct learn…
Data-Efficient Image Quality Assessment with Attention-Panel Decoder
Guanyi Qin, Runze Hu, Yutao Liu +4
Blind Image Quality Assessment (BIQA) is a fundamental task in computer vision, which however remains unresolved due to the complex distortion conditions and diversified image cont…