159 citations · 293 across the 76 of their papers we have counts for
82 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…
CamWorldQA: Perceptual Quality Assessment of Camera-Controlled World Video Generation
Yunhe Li, Likun Wu, Sijing Wu +5
Recent advances in generative video models have enabled camera-controlled world video generation, allowing models to synthesize videos under user-defined camera trajectories. Howev…
FMReward: Aligning and Evaluating Audio-Driven 3D Facial Animation with Human Preferences
Sijing Wu, Yunhao Li, Zhilin Gao +4
Audio-driven 3D facial animation is essential for advancing immersion and interactivity in virtual experiences. Although recent advances have shown promising capabilities, the trai…
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…
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…
LL-Bench: Rethinking Low-Level Vision Evaluation in the Era of Large-Scale Generative Models
Lu Liu, Huiyu Duan, Chenxin Zhu +6
Large-scale generative models have demonstrated remarkable capabilities across image generation and editing tasks. However, their performance in low-level vision tasks, which requi…
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…
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…
EditHF-1M: A Million-Scale Rich Human Preference Feedback for Image Editing
Zitong Xu, Huiyu Duan, Zhongpeng Ji +9
Recent text-guided image editing (TIE) models have achieved remarkable progress, while many edited images still suffer from issues such as artifacts, unexpected editings, unaesthet…
Learning to Wander: Improving the Global Image Geolocation Ability of LMMs via Actionable Reasoning
Yushuo Zheng, Huiyu Duan, Zicheng Zhang +2
Geolocation, the task of identifying the geographic location of an image, requires abundant world knowledge and complex reasoning abilities. Though advanced large multimodal models…
Steering and Rectifying Latent Representation Manifolds in Frozen Multi-modal LLMs for Video Anomaly Detection
Zhaolin Cai, Fan Li, Huiyu Duan +2
Video anomaly detection (VAD) aims to identify abnormal events in videos. Traditional VAD methods generally suffer from the high costs of labeled data and full training, thus some…
EEmo-Logic: A Unified Dataset and Multi-Stage Framework for Comprehensive Image-Evoked Emotion Assessment
Lancheng Gao, Ziheng Jia, Zixuan Xing +4
Understanding the multi-dimensional attributes and intensity nuances of image-evoked emotions is pivotal for advancing machine empathy and empowering diverse human-computer interac…
VideoAesBench: Benchmarking the Video Aesthetics Perception Capabilities of Large Multimodal Models
Yunhao Li, Sijing Wu, Zhilin Gao +5
Large multimodal models (LMMs) have demonstrated outstanding capabilities in various visual perception tasks, which has in turn made the evaluation of LMMs significant. However, th…
SFQA: A Comprehensive Perceptual Quality Assessment Dataset for Singing Face Generation
Zhilin Gao, Yunhao Li, Sijing Wu +3
The Talking Face Generation task has enormous potential for various applications in digital humans and agents, etc. Singing, as a common facial movement second only to talking, can…