11 citations · 17 across the 11 of their papers we have counts for
11 papers
Social-MAE: Social Masked Autoencoder for Multi-person Motion Representation Learning
Mahsa Ehsanpour, Ian Reid, Hamid Rezatofighi
For a complete comprehension of multi-person scenes, it is essential to go beyond basic tasks like detection and tracking. Higher-level tasks, such as understanding the interaction…
JRDB-Social: A Multifaceted Robotic Dataset for Understanding of Context and Dynamics of Human Interactions Within Social Groups
Simindokht Jahangard, Zhixi Cai, Shiki Wen +1
Understanding human social behaviour is crucial in computer vision and robotics. Micro-level observations like individual actions fall short, necessitating a comprehensive approach…
JRDB-PanoTrack: An Open-world Panoptic Segmentation and Tracking Robotic Dataset in Crowded Human Environments
Duy-Tho Le, Chenhui Gou, Stavya Datta +4
Autonomous robot systems have attracted increasing research attention in recent years, where environment understanding is a crucial step for robot navigation, human-robot interacti…
Improving Visual Perception of a Social Robot for Controlled and In-the-wild Human-robot Interaction
Wangjie Zhong, Leimin Tian, Duy Tho Le +1
Social robots often rely on visual perception to understand their users and the environment. Recent advancements in data-driven approaches for computer vision have demonstrated gre…
JRDB-Traj: A Dataset and Benchmark for Trajectory Forecasting in Crowds
Saeed Saadatnejad, Yang Gao, Hamid Rezatofighi +1
Predicting future trajectories is critical in autonomous navigation, especially in preventing accidents involving humans, where a predictive agent's ability to anticipate in advanc…
Physically Plausible 3D Human-Scene Reconstruction from Monocular RGB Image using an Adversarial Learning Approach
Sandika Biswas, Kejie Li, Biplab Banerjee +2
Holistic 3D human-scene reconstruction is a crucial and emerging research area in robot perception. A key challenge in holistic 3D human-scene reconstruction is to generate a physi…