240 citations · 1.3k across the 195 of their papers we have counts for
205 papers
EmoGenie: Benchmarking and Evaluating Expressed and Evoked Emotion in T2I Generation with MLLMs
Zixuan Xing, Lancheng Gao, Shengyan Li +4
Rapid advances in artificial intelligence-generated content (AIGC) have significantly promoted using text-to-image (T2I) models to generate images with specific affective intention…
Harnessing Multimodal Large Language Models for Training-Free Human-Object Interaction Detection
Zhaolin Cai, Huiyu Duan, Liu Yang +5
Human-object interaction (HOI) detection aims to localize human-object pairs and recognize their interactions. Traditional supervised methods perform strongly but rely on task-spec…
Evaluating the Evaluators: Diagnosing Large Multimodal Models for AI-Generated Image Assessment
Yu Zhao, Jiarui Wang, Huiyu Duan +5
With the rapid advancement of text-to-image (T2I) generation, robust evaluation becomes critical yet challenging, as traditional metrics fail to capture fine-grained alignment and…
Invisible in Space, Visible in Time: Motion Vision CAPTCHA against GUI Agents
Zeyu Zhang, Dingyi Rong, Zijian Chen +3
Most existing visual CAPTCHAs remain spatially solvable: the required information is exposed by static appearance, local structure, and interface state. This assumption is weakened…
LLaVA-Assessor: Building the Foundation LMM For Visual Quality Assessment
Ziheng Jia, Zicheng Zhang, Jiaying Qian +2
Aligning with the human visual system~(HVS) in perceiving and evaluating the quality of visual signals is a central objective of machine-vision-based visual quality assessment syst…
TREND-10K: A Comprehensive Dataset for Next-Generation Video Quality Assessment Based on Preference-Driven Media
Ziheng Jia, Zicheng Zhang, Junqi Zhang +4
The increasing prominence of short-video platforms, coupled with the advanced commercialization of AI-generated content (AIGC) videos, has led to a shift in the types of video medi…
Emo-Bench: A Scalable Benchmark for Multimodal Evoked and Expressed Emotion Understanding via Bayesian Pairwise Alignment
Lancheng Gao, Ziheng Jia, Shengyan Li +4
Understanding both expressed and evoked emotions is critical for multimodal large language models (MLLMs) to achieve comprehensive affect-aware interactions. However, existing benc…
Visual Distortion Detection in UGC Images Using Large Multimodal Models
Ziheng Jia, Yingji Liang, Jiaying Qian +1
The localized depiction of perceptual quality has long been a crucial, yet underexplored, challenge in image quality assessment (IQA). Existing approaches based on large multimodal…
RAVEN-Eval: Rubric-Guided Automatic Evaluation for AI Video Generation Models Based on LMM Preference Judgement
Ziheng Jia, Jiaying Qian, Zicheng Zhang +3
AI video generation has advanced rapidly and entered widespread commercial use. As a result, quality differences among videos produced by state-of-the-art AI video generation model…
MIEScore: Human-Aligned Evaluation for Multi-Source Image Editing
Zitong Xu, Huiyu Duan, Xinyun Zhang +7
Recent advances in unified multimodal models have significantly improved text-guided image editing abilities. In particular, models such as Nano-Banana-Pro and GPT-Image-2 demonstr…
Multi-Dimensional Quality Assessment for AI-Generated Human-Centric Videos: Dataset and Model
Sijing Wu, Yunhao Li, Huiyu Duan +4
AI-generated human-centric videos play a crucial role in a wide range of modern applications. However, they often suffer from quality issues and semantic mismatches, underscoring t…
From Open Loop to Closed Loop: A Test-Time Iterative Optimization Framework for Reference-Consistent Image Generation
Baixuan Zhao, Xinyu Zhang, Huayu Zheng +4
While controllable image generation has made significant strides by incorporating visual reference conditions, existing methods predominantly operate as open-loop systems. They inj…
ICME 2026 Grand Challenge on Cross-Scenario Defect Detection and Fine-Grained Severity Grading for High-Precision Manufacturing
Wei Sun, Weixia Zhang, Linhan Cao +30
This paper presents the IEEE International Conference on Multimedia and Expo (ICME) 2026 Grand Challenge on Cross-Scenario Defect Detection and Fine-Grained Severity Grading for Hi…
DyCoRM: Dynamic Criterion-Aware Reward Modeling for Text-to-Image Generation
Jiaying Qian, Ziheng Jia, Qian Zhang +5
With the continued advancement of text-to-image (T2I) generation, producing high-quality images is becoming increasingly attainable; consequently, user demands are shifting toward…
GeoR-Bench: Evaluating Geoscience Visual Reasoning
Yushuo Zheng, Zicheng Zhang, Huiyu Duan +7
Geoscience intelligence is expected to understand, reason about, and predict earth system changes to support human decision-making in critical domains such as disaster response, cl…
ReasonEdit: Towards Interpretable Image Editing Evaluation via Reinforcement Learning
Honghua Chen, Zitong Xu, Huiyu Duan +3
Recent text-guided image editing (TIE) models have achieved remarkable progress, however, many edited results still suffer from artifacts, unintended modifications, and suboptimal…
EditRefiner: A Human-Aligned Agentic Framework for Image Editing Refinement
Zitong Xu, Huiyu Duan, Yifei Nie +9
Recent text-guided image editing (TIE) models have made remarkable progress, yet edited images still frequently suffer from fine-grained issues such as unnatural objects, lighting…
DynT2I-Eval: A Dynamic Evaluation Framework for Text-to-Image Models
Juntong Wang, Jiarui Wang, Huiyu Duan +3
Existing text-to-image (T2I) benchmarks largely rely on fixed prompt sets, leaving them vulnerable to overfitting and benchmark contamination once publicly released and repeatedly…
LoViF 2026 The First Challenge on Holistic Quality Assessment for 4D World Model (PhyScore)
Wei Luo, Yiting Lu, Xin Li +32
This paper reports on the LoViF 2026 PhyScore challenge, a competition on holistic quality assessment of world-model-generated videos across both 2D and 4D generation settings. The…
Market-Bench: Benchmarking Large Language Models on Economic and Trade Competition
Yushuo Zheng, Huiyu Duan, Zicheng Zhang +3
The ability of large language models (LLMs) to manage and acquire economic resources remains unclear. In this paper, we introduce \textbf{Market-Bench}, a comprehensive benchmark t…
ITIScore: An Image-to-Text-to-Image Rating Framework for the Image Captioning Ability of MLLMs
Zitong Xu, Huiyu Duan, Shengyao Qin +6
Recent advances in multimodal large language models (MLLMs) have greatly improved image understanding and captioning capabilities. However, existing image captioning benchmarks typ…
VidAudio-Bench: Benchmarking V2A and VT2A Generation across Four Audio Categories
Qian Zhang, Yuqin Cao, Yixuan Gao +1
Video-to-Audio (V2A) generation is essential for immersive multimedia experiences, yet its evaluation remains underexplored. Existing benchmarks typically assess diverse audio type…
Evaluating Image Editing with LLMs: A Comprehensive Benchmark and Intermediate-Layer Probing Approach
Shiqi Gao, Zitong Xu, Kang Fu +3
Evaluating text-guided image editing (TIE) methods remains a challenging problem, as reliable assessment should simultaneously consider perceptual quality, alignment with textual i…
Preference-Guided Debiasing for No-Reference Enhancement Image Quality Assessment
Shiqi Gao, Kang Fu, Zitong Xu +4
Current no-reference image quality assessment (NR-IQA) models for enhanced images often struggle to generalize, as they tend to overfit to the distinct patterns of specific enhance…