papers

Publications (8)

cs.CV2024

Modeling Multimodal Social Interactions: New Challenges and Baselines with Densely Aligned Representations

Sangmin Lee, Bolin Lai, Fiona Ryan +2

Understanding social interactions involving both verbal and non-verbal cues is essential for effectively interpreting social situations. However, most prior works on multimodal soc…

cs.CV2024

Ego-Exo4D: Understanding Skilled Human Activity from First- and Third-Person Perspectives

Kristen Grauman, Andrew Westbury, Lorenzo Torresani +98

We present Ego-Exo4D, a diverse, large-scale multimodal multiview video dataset and benchmark challenge. Ego-Exo4D centers around simultaneously-captured egocentric and exocentric…

cs.LG2021

Multipath Graph Convolutional Neural Networks

Rangan Das, Bikram Boote, Saumik Bhattacharya +1

Graph convolution networks have recently garnered a lot of attention for representation learning on non-Euclidean feature spaces. Recent research has focused on stacking multiple l…

cs.CV2024

Leveraging Object Priors for Point Tracking

Bikram Boote, Anh Thai, Wenqi Jia +4

Point tracking is a fundamental problem in computer vision with numerous applications in AR and robotics. A common failure mode in long-term point tracking occurs when the predicte…

cs.HC2024

Towards Social AI: A Survey on Understanding Social Interactions

Sangmin Lee, Minzhi Li, Bolin Lai +8

Social interactions form the foundation of human societies. Artificial intelligence has made significant progress in certain areas, but enabling machines to seamlessly understand s…

cs.CV2026

GRASP: Learning to Ground Social Reasoning in Multi-Person Non-Verbal Interactions

Junho Kim, Xu Cao, Houze Yang +6

Understanding social interactions requires reasoning over subtle non-verbal cues, yet current multimodal large language models (MLLMs) often fail to identify who interacts with who…

cs.CV2026

MEBench: A Novel Benchmark for Understanding Mutual Exclusivity Bias in Vision-Language Models

Anh Thai, Stefan Stojanov, Zixuan Huang +2

This paper introduces MEBench, a novel benchmark for evaluating mutual exclusivity (ME) bias, a cognitive phenomenon observed in children during word learning. Unlike traditional M…

cs.CV2023

Low-shot Object Learning with Mutual Exclusivity Bias

Anh Thai, Ahmad Humayun, Stefan Stojanov +3

This paper introduces Low-shot Object Learning with Mutual Exclusivity Bias (LSME), the first computational framing of mutual exclusivity bias, a phenomenon commonly observed in in…