activity
20232026
most citedQ-Align: Teaching LMMs for Visual Scoring via Discrete Text-Defined Levels

33 citations · 69 across the 40 of their papers we have counts for

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Showing 2025Show all

9 papers · 1 filter

cs.CV2025

Embodied Image Compression

Chunyi Li, Rui Qing, Jianbo Zhang +6

Image Compression for Machines (ICM) has emerged as a pivotal research direction in the field of visual data compression. However, with the rapid evolution of machine intelligence,…

cs.CV2025

Using GUI Agent for Electronic Design Automation

Chunyi Li, Longfei Li, Zicheng Zhang +4

Graphical User Interface (GUI) agents adopt an end-to-end paradigm that maps a screenshot to an action sequence, thereby automating repetitive tasks in virtual environments. Howeve…

cs.CV2025

OmniQuality-R: Advancing Reward Models Through All-Encompassing Quality Assessment

Yiting Lu, Fengbin Guan, Yixin Gao +8

Current visual evaluation approaches are typically constrained to a single task. To address this, we propose OmniQuality-R, a unified reward modeling framework that transforms mult…

cs.CV2025

Just Noticeable Difference for Large Multimodal Models

Zijian Chen, Yuan Tian, Yuze Sun +5

Just noticeable difference (JND), the minimum change that the human visual system (HVS) can perceive, has been studied for decades. Although recent work has extended this line of r…

cs.CV2025

LMM4Edit: Benchmarking and Evaluating Multimodal Image Editing with LMMs

Zitong Xu, Huiyu Duan, Bingnan Liu +9

The rapid advancement of Text-guided Image Editing (TIE) enables image modifications through text prompts. However, current TIE models still struggle to balance image quality, edit…

cs.CV2025

Image Quality Assessment for Embodied AI

Chunyi Li, Jiaohao Xiao, Jianbo Zhang +8

Embodied AI has developed rapidly in recent years, but it is still mainly deployed in laboratories, with various distortions in the Real-world limiting its application. Traditional…

cs.CV2025

Q-Adapt: Adapting LMM for Visual Quality Assessment with Progressive Instruction Tuning

Yiting Lu, Xin Li, Haoning Wu +3

The rapid advancement of Large Multi-modal Foundation Models (LMM) has paved the way for the possible Explainable Image Quality Assessment (EIQA) with instruction tuning from two p…

cs.CV2025

Image Quality Assessment: From Human to Machine Preference

Chunyi Li, Yuan Tian, Xiaoyue Ling +9

Image Quality Assessment (IQA) based on human subjective preferences has undergone extensive research in the past decades. However, with the development of communication protocols,…

cs.CV2025

Q-SiT: Teaching LMMs for Image Quality Scoring and Interpreting

Zicheng Zhang, Haoning Wu, Ziheng Jia +2

Image quality scoring and interpreting are two fundamental components of Image Quality Assessment (IQA). The former quantifies image quality, while the latter enables descriptive q…