Qiaohui Chu — accepted AI-conference papers

2026

Exo2Ego: Exocentric Knowledge Guided MLLM for Egocentric Video Understanding

Haoyu Zhang, Qiaohui Chu, Meng Liu, Haoxiang Shi, Yaowei Wang, Liqiang Nie

AAAI 2026technical

AI personal assistants, deployed through robots or wearables, require embodied understanding to collaborate effectively with humans. However, current Multimodal Large Language Models (MLLMs) primarily focus on third-person (exocentric) vision, overlooking the unique challenges of first-person (egoce

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2026

Intention-Guided Cognitive Reasoning for Egocentric Long-Term Action Anticipation

Qiaohui Chu, Haoyu Zhang, Meng Liu, Yisen Feng, Haoxiang Shi, Liqiang Nie

AAAI 2026technical

Long-term action anticipation from egocentric video is critical for applications such as human-computer interaction and assistive technologies, where anticipating user intent enables proactive and context-aware AI assistance. However, existing approaches suffer from three key limitations: 1) underut

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