Search Results for author:
Found 4 papers, 1 papers with code
MultiPath++: Efficient Information Fusion and Trajectory Aggregation for Behavior Prediction
Predicting the future behavior of road users is one of the most challenging and important problems in autonomous driving.
Ranked #16 on
Motion Forecasting
on Argoverse CVPR 2020
Multi-modal 3D Human Pose Estimation with 2D Weak Supervision in Autonomous Driving
3D human pose estimation (HPE) in autonomous vehicles (AV) differs from other use cases in many factors, including the 3D resolution and range of data, absence of dense depth maps, failure modes for LiDAR, relative location between the camera and LiDAR, and a high bar for estimation accuracy.
JFP: Joint Future Prediction with Interactive Multi-Agent Modeling for Autonomous Driving
We propose JFP, a Joint Future Prediction model that can learn to generate accurate and consistent multi-agent future trajectories.
MotionDiffuser: Controllable Multi-Agent Motion Prediction using Diffusion
We present MotionDiffuser, a diffusion based representation for the joint distribution of future trajectories over multiple agents.
