Human-object interaction (HOI) detection aims to localize human-object pairs and recognize their interactions. Traditional supervised methods perform strongly but rely on task-specific training. Recent multimodal large language models (MLLMs) offer a promising route to training-free HOI detection through their broad vi...
Zhao-Lin Cai, Hui-Yu Duan, Liu Yang et al.· 0 citations
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 models~(AIVGMs) have become increasingly difficult to discern using conventional evaluation criteria, such as visual fidelity and semantic instru...
Zi-Heng Jia, Jia-Ying Qian, Zi-Cheng Zhang et al.· 0 citations
This work introduces SQUARE-Bench, a comprehensive benchmark that systematically evaluates LMM capabilities as evaluators of AI-generated images across four aspects: Semantics, Quality, Authenticity, and Responsibility, and conducts a proof-of-concept study of LMM-guided iterative editing.
Yu Zhao, Jia-Rui Wang, Hui-Yu Duan et al.· 0 citations
This work proposes LLaVA-Assessor, a unified data construction and model training system for LMM-based machine vision, and introduces a simple yet effective prompt disentanglement strategy to alleviate training-objective confusion in multi-task learning, thereby enabling stable and coherent joint training.
Zi-Heng Jia, Zi-Cheng Zhang, Jia-Ying Qian et al.· 0 citations
TREND-10K is introduced, a next-generation comprehensive VQA dataset consisting of the trend-driven part and the static part, containing $10,000$ videos across a wide spectrum of content types, and presents a robust framework for advancing VQA, addressing challenges caused by the temporal evolution of user perceptual h...
Zi-Heng Jia, Zi-Cheng Zhang, Jun-Qi Zhang et al.· 0 citations
This work extends the previous dataset HVEval with pairwise preference annotations and proposes MoE-Rater, a Mixture-of-Experts (MoE)-inspired and multimodal large language model (MLLM)-based all-in-one method that supports multi-dimensional quality rating, multi-dimensional pairwise comparison, and category-specific q...
Si-Jing Wu, Yun-Hao Li, Hui-Yu Duan et al.· IEEE transactions on circuit...· 4 citations
MIE-Bench is introduced, the first large-scale multiple image editing benchmark with fine-grained human preference annotations and MIEScore, a multimodal large language model (MLLM)-based evaluation model enhanced with skill optimization and multi-dimensional supervised fine-tuning, to provide human-aligned feedback fo...
Zi-Tong Xu, Huiyu Duan, Xinyu Zhang et al.· 0 citations
This model leverages different layers of the large language model (LLM) decoder, treating them as multiple detectors that perform synchronous distortion detection using multi-level features, which helps mitigate the ambiguous foreground-background separation commonly encountered in the S2A problem.
Zi-Heng Jia, Yingji Liang, Jia-Ying Qian et al.· 0 citations
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