realsense explorer botAutonomous ground exploration mobile robot which has 3-DOF manipulator with Intel Realsense D435i mounted on a Tracked skid-steer drive mobile robot. The robot is capable of mapping spaces, exploration through RRT, SLAM and 3D pose estimation of objects around it. This is an custom robot with self built URDF model.The Robot uses ROS's navigation…
Stars: ✭ 61 (+3.39%)
openpilotEasy Driving~!!
Stars: ✭ 36 (-38.98%)
pyMHTTrack oriented, multi target, multi hypothesis tracker
Stars: ✭ 66 (+11.86%)
video featuresExtract video features from raw videos using multiple GPUs. We support RAFT and PWC flow frames as well as S3D, I3D, R(2+1)D, VGGish, CLIP, ResNet features.
Stars: ✭ 225 (+281.36%)
highway-path-planningMy path-planning pipeline to navigate a car safely around a virtual highway with other traffic.
Stars: ✭ 39 (-33.9%)
Optical-Flow-GPU-DockerCompute dense optical flow using TV-L1 algorithm with NVIDIA GPU acceleration.
Stars: ✭ 48 (-18.64%)
loco carSoftware for LOCO, our autonomous drifting RC car.
Stars: ✭ 44 (-25.42%)
community-projectsWebots projects (PROTO files, controllers, simulation worlds, etc.) contributed by the community.
Stars: ✭ 20 (-66.1%)
glcapsnetGlobal-Local Capsule Network (GLCapsNet) is a capsule-based architecture able to provide context-based eye fixation prediction for several autonomous driving scenarios, while offering interpretability both globally and locally.
Stars: ✭ 33 (-44.07%)
Maskflownet[CVPR 2020, Oral] MaskFlownet: Asymmetric Feature Matching with Learnable Occlusion Mask
Stars: ✭ 242 (+310.17%)
self-driving-carImplementation of the paper "End to End Learning for Self-Driving Cars"
Stars: ✭ 54 (-8.47%)
EPCEvery Pixel Counts ++: Joint Learning of Geometry and Motion with 3D Holistic Understanding
Stars: ✭ 27 (-54.24%)
odometryTraining Deep SLAM on Single Frames https://arxiv.org/abs/1912.05405
Stars: ✭ 38 (-35.59%)
GuidedNetCaffe implementation for "Guided Optical Flow Learning"
Stars: ✭ 28 (-52.54%)
BridgeDepthFlowBridging Stereo Matching and Optical Flow via Spatiotemporal Correspondence, CVPR 2019
Stars: ✭ 114 (+93.22%)
simple-sfmA readable implementation of structure-from-motion
Stars: ✭ 19 (-67.8%)
rgbd odometryNo description or website provided.
Stars: ✭ 22 (-62.71%)
SubjuGatorSubjuGator 8 on-board software
Stars: ✭ 31 (-47.46%)
Visualizing-lidar-dataVisualizing lidar data using Uber Autonomous Visualization System (AVS) and Jupyter Notebook Application
Stars: ✭ 75 (+27.12%)
dreyeve[TPAMI 2018] Predicting the Driver’s Focus of Attention: the DR(eye)VE Project. A deep neural network learnt to reproduce the human driver focus of attention (FoA) in a variety of real-world driving scenarios.
Stars: ✭ 88 (+49.15%)
can-goController Area Network (CAN) SDK for Go.
Stars: ✭ 113 (+91.53%)
PyTrxPyTrx is a Python object-oriented programme created for the purpose of calculating real-world measurements from oblique images and time-lapse image series. Its primary purpose is to obtain velocities, surface areas, and distances from oblique, optical imagery of glacial environments.
Stars: ✭ 31 (-47.46%)
FMT-FirmwareFMT Autopilot Embedded System
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UnflowUnFlow: Unsupervised Learning of Optical Flow with a Bidirectional Census Loss
Stars: ✭ 239 (+305.08%)
correlation flowROS package for Correlation Flow (ICRA 2018)
Stars: ✭ 28 (-52.54%)
CorrelationLayerPure Pytorch implementation of Correlation Layer that commonly used in learning based optical flow estimator
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SoftNet-SpotMEShallow Optical Flow Three-Stream CNN For Macro and Micro-Expression Spotting From Long Videos
Stars: ✭ 17 (-71.19%)
GndNetGndNet: Fast ground plane estimation and point cloud segmentation for autonomous vehicles using deep neural networks.
Stars: ✭ 113 (+91.53%)
SelfDrivingRCCarAutonomous RC Car using Neural Networks, Python and Open CV
Stars: ✭ 102 (+72.88%)
Model-Predictive-ControlThis project is to use Model Predictive Control (MPC) to drive a car in a game simulator. The server provides reference waypoints (yellow line in the demo video) via websocket, and we use MPC to compute steering and throttle commands to drive the car. The solution must be robust to 100ms latency, since it might encounter in real-world application.
Stars: ✭ 93 (+57.63%)
flow1d[ICCV 2021 Oral] High-Resolution Optical Flow from 1D Attention and Correlation
Stars: ✭ 91 (+54.24%)
OpenpilotToolkitOpenpilot Toolkit (OPTK) is a class library and toolkit for interacting with your openpilot / commaai devices.
Stars: ✭ 55 (-6.78%)
humanflow2Official repository of Learning Multi-Human Optical Flow (IJCV 2019)
Stars: ✭ 37 (-37.29%)
EPPMCUDA implementation of the paper "Fast Edge-Preserving PatchMatch for Large Displacement Optical Flow" in CVPR 2014.
Stars: ✭ 34 (-42.37%)
JuliaAutonomyJulia sample codes for Autonomy, Robotics and Self-Driving Algorithms.
Stars: ✭ 21 (-64.41%)
drift drlHigh-speed Autonomous Drifting with Deep Reinforcement Learning
Stars: ✭ 82 (+38.98%)
CrowdFlowOptical Flow Dataset and Benchmark for Visual Crowd Analysis
Stars: ✭ 87 (+47.46%)
flow-io-opencvFork and OpenCV wrapper of the optical flow I/O and visualization code provided as part of the Sintel dataset [1].
Stars: ✭ 20 (-66.1%)
SCUTTLESCUTTLE™: Sensing, Connected, Utility Transport Taxi for Level Environments [An open-source Mobile Robot]
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mmflowOpenMMLab optical flow toolbox and benchmark
Stars: ✭ 711 (+1105.08%)
deepOFTensorFlow implementation for "Guided Optical Flow Learning"
Stars: ✭ 26 (-55.93%)
wasr networkWaSR Segmentation Network for Unmanned Surface Vehicles v0.5
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Awesome-Self-Drivingan awesome list of self-driving algorithms, software, tools
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flowattackAttacking Optical Flow (ICCV 2019)
Stars: ✭ 58 (-1.69%)
ACSCAutomatic Calibration for Non-repetitive Scanning Solid-State LiDAR and Camera Systems
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PCLNetUnsupervised Learning for Optical Flow Estimation Using Pyramid Convolution LSTM.
Stars: ✭ 29 (-50.85%)
dig-into-apolloApollo notes (Apollo学习笔记) - Apollo learning notes for beginners.
Stars: ✭ 1,786 (+2927.12%)
Auto-Birds-EyeBird's eye/Top Down view generation and mapping with deep learning.
Stars: ✭ 129 (+118.64%)
TonicAn autonomous vehicle written in python
Stars: ✭ 85 (+44.07%)
AdverseDriveAttacking Vision based Perception in End-to-end Autonomous Driving Models
Stars: ✭ 24 (-59.32%)