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apollo

An open autonomous driving platform

apollo-note

Note for Apollo 3.0 perception, prediction and planning modules

autoware

Open-source software for urban autonomous driving

bindsnet

Simulation of spiking neural networks (SNNs) using PyTorch.

brian2

Brian is a free, open source simulator for spiking neural networks.

carla_ray_rlib

Carla-Simulator environment compatible with Ray/Rllib

computer_vision_using_tensorflowlite

On this project, AlexNet Convolution Neural Network is trained using traffic sign images from the German Road Traffic Sign Benchmark. The initially trained network is then quantized and optimized for deployment on mobile devices using TensorFlow Lite

conf-net

Predicting Depth Completion Error-Map For High-Confidence Dense 3D Point-Cloud

deepo

A Docker image containing almost all popular deep learning frameworks: theano, tensorflow, sonnet, pytorch, keras, lasagne, mxnet, cntk, chainer, caffe, torch.

evt-mnist

This is an event-driven version of MNIST dataset which can be used to evaluating spiking neural network's accuracy

fixedwing-airsim

Combines JSBSim and Airsim with a python module to simulate a fixedwing

imudb

[RA-L 2023] Official Pytorch-Lightning Implementation for "A Simple Self-Supervised IMU Denoising Method For Inertial Aided Navigation", in IEEE Robotics and Automation Letters, 2023

pysnn

Efficient Spiking Neural Network framework, built on top of PyTorch for GPU acceleration

reinforcement-learning

Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.

rpg_eklt

Code for the paper "EKLT: Asynchronous, Photometric Feature Tracking using Events and Frames" (IJCV'19)

slayerpytorch

PyTorch implementation of SLAYER for training Spiking Neural Networks

snn_benchmark

snn_cv_applications_resources

Paper list for SNN based computer vision tasks.

social-nce

[ICCV21] Official implementation of the "Social NCE: Contrastive Learning of Socially-aware Motion Representations" in PyTorch.

trajectron-plus-plus

Code accompanying "Trajectron++: Dynamically-Feasible Trajectory Forecasting With Heterogeneous Data" by Tim Salzmann*, Boris Ivanovic*, Punarjay Chakravarty, and Marco Pavone (* denotes equal contribution).