TORCS Dataset Papers With Code

TORCS (The Open Racing Car Simulator) is a driving simulator. It is capable of simulating the essential elements of vehicular dynamics such as mass, rotational inertia, collision, mechanics of suspensions, links and differentials, friction and aerodynamics. Physics simulation is simplified and is carried out through Euler integration of differential equations at a temporal discretization level of 0.002 seconds. The rendering pipeline is lightweight and based on OpenGL that can be turned off for faster training. TORCS offers a large variety of tracks and cars as free assets. It also provides a number of programmed robot cars with different levels of performance that can be used to benchmark the performance of human players and software driving agents. TORCS was built with the goal of developing Artificial Intelligence for vehicular control and has been used extensively by the machine learning community ever since its inception.

CUHK03 Benchmark (Person Re-Identification)

PDF) Securing Future Autonomous & Connected Vehicles: Challenges Posed by Adversarial Machine Learning and The Way Forward

Matthew Muckley on LinkedIn: Announcing version 2.0 of the fastMRI dataset · Discussion #284 ·…

PDF] Distributed Approach for implementation of A3C on TORCS

Using Keras and Deep Deterministic Policy Gradient to play TORCS

Deep_Reinforcement_Learning_for_Autonomous_Driving_A_Survey

TFW: Annotated Thermal Faces in the Wild Dataset Dataset

PDF] Study and Comparison of General Purpose Fuzzers

GitHub - IBM/torc_py: torcpy is a platform-agnostic adaptive load balancing library that orchestrates the scheduling of task parallelism on both shared and distributed memory platforms.

Integrated omics networks reveal the temporal signaling events of brassinosteroid response in Arabidopsis