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Found 9 papers, 3 papers with code
Towards a Mechanistic Explanation of Diffusion Model Generalization
We propose a mechanism for diffusion generalization based on local denoising operations.
TorchDriveEnv: A Reinforcement Learning Benchmark for Autonomous Driving with Reactive, Realistic, and Diverse Non-Playable Characters
Moreover, because of the high variability between different problems presented in different autonomous systems, these simulators need to be easy to use, and easy to modify.
Semantically Consistent Video Inpainting with Conditional Diffusion Models
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 across frames.
Nearest Neighbour Score Estimators for Diffusion Generative Models
Score function estimation is the cornerstone of both training and sampling from diffusion generative models.
Realistically distributing object placements in synthetic training data improves the performance of vision-based object detection models
When training object detection models on synthetic data, it is important to make the distribution of synthetic data as close as possible to the distribution of real data.
Video Killed the HD-Map: Predicting Multi-Agent Behavior Directly From Aerial Images
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.
Conditional Permutation Invariant Flows
We present a novel, conditional generative probabilistic model of set-valued data with a tractable log density.
Critic Sequential Monte Carlo
We introduce CriticSMC, a new algorithm for planning as inference built from a composition of sequential Monte Carlo with learned Soft-Q function heuristic factors.
Predicting Motion of Vulnerable Road Users using High-Definition Maps and Efficient ConvNets
Following detection and tracking of traffic actors, prediction of their future motion is the next critical component of a self-driving vehicle (SDV) technology, allowing the SDV to operate safely and efficiently in its environment.
