As mobile robots are increasingly introduced into our daily lives, it grows ever more
imperative that these robots navigate with and among people in a safe and socially …

AI is undergoing a paradigm shift with the rise of models (eg, BERT, DALL-E, GPT-3) that are
trained on broad data at scale and are adaptable to a wide range of downstream tasks. We …

We show, for the first time, that neural networks trained only on synthetic data achieve state-
of-the-art accuracy on the problem of 3D human pose and shape (HPS) estimation from real …

We present BEHAVIOR-1K, a comprehensive simulation benchmark for human-centered
robotics. BEHAVIOR-1K includes two components, guided and motivated by the results of an …

We introduce BEHAVIOR, a benchmark for embodied AI with 100 activities in simulation,
spanning a range of everyday household chores such as cleaning, maintenance, and food …

Social navigation is the capability of an autonomous agent, such as a robot, to navigate in a
“socially compliant” manner in the presence of other intelligent agents such as humans. With …

Recently, fusing the LiDAR point cloud and camera image to improve the performance and
robustness of 3D object detection has received more and more attention, as these two …

Recent developments in monocular multi-object tracking have been very successful in
tracking visible objects and bridging short occlusion gaps, mainly relying on data-driven …

Autonomous robotic systems operating in human environments must understand their
surroundings to make accurate and safe decisions. In crowded human scenes with close-up …

Humans naturally perceive surrounding scenes by unifying sound and sight in a first-person
view. Likewise, machines are advanced to approach human intelligence by learning with …