79 citations · 105 across the 12 of their papers we have counts for
13 papers
Overcoming Multi-step Complexity in Multimodal Theory-of-Mind Reasoning: A Scalable Bayesian Planner
Chunhui Zhang, Zhongyu Ouyang, Kwonjoon Lee +4
Theory-of-Mind (ToM) enables humans to infer mental states-such as beliefs, desires, and intentions-forming the foundation of social cognition. However, existing computational ToM…
M2D2M: Multi-Motion Generation from Text with Discrete Diffusion Models
Seunggeun Chi, Hyung-gun Chi, Hengbo Ma +4
We introduce the Multi-Motion Discrete Diffusion Models (M2D2M), a novel approach for human motion generation from textual descriptions of multiple actions, utilizing the strengths…
Can't make an Omelette without Breaking some Eggs: Plausible Action Anticipation using Large Video-Language Models
Himangi Mittal, Nakul Agarwal, Shao-Yuan Lo +1
We introduce PlausiVL, a large video-language model for anticipating action sequences that are plausible in the real-world. While significant efforts have been made towards anticip…
Vamos: Versatile Action Models for Video Understanding
Shijie Wang, Qi Zhao, Minh Quan Do +3
What makes good representations for video understanding, such as anticipating future activities, or answering video-conditioned questions? While earlier approaches focus on end-to-…
Object-centric Video Representation for Long-term Action Anticipation
Ce Zhang, Changcheng Fu, Shijie Wang +4
This paper focuses on building object-centric representations for long-term action anticipation in videos. Our key motivation is that objects provide important cues to recognize an…
AntGPT: Can Large Language Models Help Long-term Action Anticipation from Videos?
Qi Zhao, Shijie Wang, Ce Zhang +5
Can we better anticipate an actor's future actions (e.g. mix eggs) by knowing what commonly happens after his/her current action (e.g. crack eggs)? What if we also know the longer-…