World Action Models (WAMs), often built upon pretrained video-generation world models, have emerged as a promising framework for general-purpose and open-ended robot control. However, their real-world deployment often suffers from discontinuous and jerky execution. Existing methods typically address this issue by eithe...
Shao-Jie Ren, Jing-Wen Sun, Ze-Zhi Liu et al.· 0 citations
Long-form video understanding often involves multiple questions about different aspects of the same recording. Yet existing video agents typically process each question through an isolated tool-use trajectory. This repeatedly restarts video exploration and memory construction, missing opportunities to acquire evidence...
Run-Quan Gui, Han-Zhu Chen, Ze-Hao Wang et al.· 0 citations
VideoTok4D, a novel 4D-aware video tokenizer for compact world representation that achieves state-of-the-art performance while requiring up to 4 orders of magnitude less storage than dense 4D representations, and substantially shortens diffusion sequences, enabling efficient generation.
Xin-Yi Chen, Han-Xin Zhu, Xi-Jun Wang et al.· 1 citation
Text-driven instruction-based video editing in complex scenes remains challenging: purely textual prompts often fail to capture precise spatial relationships and physical constraints, resulting in target ambiguity and physically implausible outcomes. To address this, we propose a plan--guide--edit framework that explic...
Sen Liang, Fengbin Guan, Youliang Zhang et al.· 5 citations
This work presents Inter-X++, a comprehensive and large-scale benchmark designed to empower versatile HHI analysis, and proposes OpenHHI, a single and unified HHI representation and modeling framework that jointly optimizes interaction reconstruction and semantic understanding.
Liang Xu, Cheng-Qun Yang, Zili Lin et al.· 0 citations
IMPACT is introduced, a scalable Interaction-aware Model training framework with Prior-guided Attention Calibration and Targeting, which consistently outperforms the corresponding MSE-trained baselines, improving interaction fidelity, physical plausibility, and visual quality.
Rong-Ze Tang, Jian-Jie Fang, Zhao-Lu Wang et al.· 1 citation
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