5 accepted papers
``Read the room,'' or the ability to infer others' mental states from subtle social cues, is a hallmark of human social intelligence but remains a major challenge for current AI systems. Existing social reasoning datasets are limited in complexity, scale, and coverage of mental states, falling short…
Pedestrian trajectory prediction is crucial for many intelligent tasks. While existing methods predict future trajectories from fixed-frame historical observations, they are limited by the observational perspective and the need for extensive historical information, resulting in prediction delays and…
In this paper, we propose a novel task IntentQA, a special VideoQA task focusing on video intent reasoning, which has become increasingly important for AI with its advantages in equipping AI agents with the capability of reasoning beyond mere recognition in daily tasks. We also contribute a large-sc…
"Video relation grounding has attracted growing attention in the fields of video understanding and multimodal learning. While the past years have witnessed remarkable progress in this issue, the difficulties of multi-instance and complex temporal reasoning make it still a challenging task. In this p…
To copy with the extreme variations of illumination and rotation in the real world, popular descriptors have captured more invariance recently, but more invariance makes descriptors less informative. So this paper designs a unique attention guided framework (named AISLFD) to select appropriate invar…