8 papers
FitAQA: A Benchmark of Fitness Action Quality Assessment for Multimodal Large Language Models
Kaili Zheng, Kaiwen Wang, Xun Zhu +3
Fitness Action Quality Assessment (AQA) is important for intelligent sports training, yet the capabilities of Multimodal Large Language Models (MLLMs) in this setting remain undere…
InterMesh: Explicit Interaction-Aware End-to-End Multi-Person Human Mesh Recovery
Kaili Zheng, Kaiwen Wang, Xun Zhu +2
Humans constantly interact with their surroundings. Existing end-to-end multi-person human mesh recovery methods, typically based on the DETR framework, capture inter-human relatio…
Collaborative Parameter Learning: Mitigating Forgetting via Parameter-Level Gradient Analysis
Mutian Yang, Zisen Zhan, Yutong Chen +7
Catastrophic forgetting during knowledge injection impairs the ability of large language models to acquire new knowledge without overwriting previously mastered knowledge. Recent s…
Lost in the Hype: Revealing and Dissecting the Performance Degradation of Medical Multimodal Large Language Models in Image Classification
Xun Zhu, Fanbin Mo, Xi Chen +6
The rise of multimodal large language models (MLLMs) has sparked an unprecedented wave of applications in the field of medical imaging analysis. However, as one of the earliest and…
BoxComm: Benchmarking Category-Aware Commentary Generation and Narration Rhythm in Boxing
Kaiwen Wang, Kaili Zheng, Rongrong Deng +3
Recent multimodal large language models (MLLMs) have shown strong capabilities in general video understanding, driving growing interest in automatic sports commentary generation. H…
BoxMind: Closed-loop AI strategy optimization for elite boxing validated in the 2024 Olympics
Kaiwen Wang, Kaili Zheng, Rongrong Deng +8
Competitive sports require sophisticated tactical analysis, yet combat disciplines like boxing remain underdeveloped in AI-driven analytics due to the complexity of action dynamics…