activity
20212024
most citedJFP: Joint Future Prediction with Interactive Multi-Agent Modeling for Autonomous Driving

7 citations · 13 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2024★ 5 cited

SceneDiffuser: Efficient and Controllable Driving Simulation Initialization and Rollout

Chiyu Max Jiang, Yijing Bai, Andre Cornman +12

Realistic and interactive scene simulation is a key prerequisite for autonomous vehicle (AV) development. In this work, we present SceneDiffuser, a scene-level diffusion prior desi…

cs.RO2023★ 1 cited

MotionDiffuser: Controllable Multi-Agent Motion Prediction using Diffusion

Chiyu Max Jiang, Andre Cornman, Cheolho Park +3

We present MotionDiffuser, a diffusion based representation for the joint distribution of future trajectories over multiple agents. Such representation has several key advantages:…

cs.MA2022★ 7 cited

JFP: Joint Future Prediction with Interactive Multi-Agent Modeling for Autonomous Driving

Wenjie Luo, Cheolho Park, Andre Cornman +2

We propose JFP, a Joint Future Prediction model that can learn to generate accurate and consistent multi-agent future trajectories. For this task, many different methods have been…

cs.CV2021

Multi-modal 3D Human Pose Estimation with 2D Weak Supervision in Autonomous Driving

Jingxiao Zheng, Xinwei Shi, Alexander Gorban +9

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,…

cs.CV2021

MultiPath++: Efficient Information Fusion and Trajectory Aggregation for Behavior Prediction

Balakrishnan Varadarajan, Ahmed Hefny, Avikalp Srivastava +8

Predicting the future behavior of road users is one of the most challenging and important problems in autonomous driving. Applying deep learning to this problem requires fusing het…