1 citations · 1 across the 9 of their papers we have counts for
9 papers
Mirror Learning
Yunpeng Liu, Matthew Niedoba, Oluwanifemi A. Adekanye +4
We investigate imitation learning through the lens of third-person observation and propose a framework for mirror learning: acquiring actionable policies from passive observation.…
Improved Constrained Generation by Bridging Pretrained Generative Models
Xiaoxuan Liang, Saeid Naderiparizi, Yunpeng Liu +2
Constrained generative modeling is fundamental to applications such as robotic control and autonomous driving, where models must respect physical laws and safety-critical constrain…
Rolling Ahead Diffusion for Traffic Scene Simulation
Yunpeng Liu, Matthew Niedoba, William Harvey +3
Realistic driving simulation requires that NPCs not only mimic natural driving behaviors but also react to the behavior of other simulated agents. Recent developments in diffusion-…
TorchDriveEnv: A Reinforcement Learning Benchmark for Autonomous Driving with Reactive, Realistic, and Diverse Non-Playable Characters
Jonathan Wilder Lavington, Ke Zhang, Vasileios Lioutas +9
The training, testing, and deployment, of autonomous vehicles requires realistic and efficient simulators. Moreover, because of the high variability between different problems pres…
Semantically Consistent Video Inpainting with Conditional Diffusion Models
Dylan Green, William Harvey, Saeid Naderiparizi +10
Current state-of-the-art methods for video inpainting typically rely on optical flow or attention-based approaches to inpaint masked regions by propagating visual information acros…
Layerwise Proximal Replay: A Proximal Point Method for Online Continual Learning
Jason Yoo, Yunpeng Liu, Frank Wood +1
In online continual learning, a neural network incrementally learns from a non-i.i.d. data stream. Nearly all online continual learning methods employ experience replay to simultan…
Nearest Neighbour Score Estimators for Diffusion Generative Models
Matthew Niedoba, Dylan Green, Saeid Naderiparizi +9
Score function estimation is the cornerstone of both training and sampling from diffusion generative models. Despite this fact, the most commonly used estimators are either biased…
A Diffusion-Model of Joint Interactive Navigation
Matthew Niedoba, Jonathan Wilder Lavington, Yunpeng Liu +8
Simulation of autonomous vehicle systems requires that simulated traffic participants exhibit diverse and realistic behaviors. The use of prerecorded real-world traffic scenarios i…
Video Killed the HD-Map: Predicting Multi-Agent Behavior Directly From Aerial Images
Yunpeng Liu, Vasileios Lioutas, Jonathan Wilder Lavington +8
The development of algorithms that learn multi-agent behavioral models using human demonstrations has led to increasingly realistic simulations in the field of autonomous driving.…