Stars
An elegant PyTorch deep reinforcement learning library.
PLUTO: Push the Limit of Imitation Learning-based Planning for Autonomous Driving
SparseDrive: End-to-End Autonomous Driving via Sparse Scene Representation
[ECCV 2024] 3D World Model for Autonomous Driving
国内首个占据栅格网络全栈课程《从BEV到Occupancy Network，算法原理与工程实践》，包含端侧部署。Surrounding Semantic Occupancy Perception Course for Autonomous Driving (docs, ppt and source code) 在线课程主页：http://111.229.117.200:8100/ (作者独立搭建)
BEVFormer inference on TensorRT, including INT8 Quantization and Custom TensorRT Plugins (float/half/half2/int8).
[ECCV 2022] This is the official implementation of BEVFormer, a camera-only framework for autonomous driving perception, e.g., 3D object detection and semantic map segmentation.
Fast-BEV: A Fast and Strong Bird’s-Eye View Perception Baseline
Awesome papers about Multi-Camera 3D Object Detection and Segmentation in Bird's-Eye-View, such as DETR3D, BEVDet, BEVFormer, BEVDepth, UniAD
A project demonstrating Lidar related AI solutions, including three GPU accelerated Lidar/camera DL networks (PointPillars, CenterPoint, BEVFusion) and the related libs (cuPCL, 3D SparseConvolution…
[CVPR 2023] An academic alternative to Tesla's occupancy network for autonomous driving.
The modified version of monodle, supports truncation targets.
Delving into Localization Errors for Monocular 3D Object Detection, CVPR'2021
Lift, Splat, Shoot: Encoding Images from Arbitrary Camera Rigs by Implicitly Unprojecting to 3D (ECCV 2020)
🔥🔥🔥🔥 (Earlier YOLOv7 not official one) YOLO with Transformers and Instance Segmentation, with TensorRT acceleration! 🔥🔥🔥
SMOKE: Single-Stage Monocular 3D Object Detection via Keypoint Estimation
Implementation of popular deep learning networks with TensorRT network definition API
A tool to modify ONNX models in a visualization fashion, based on Netron and Flask.
yolort is a runtime stack for yolov5 on specialized accelerators such as tensorrt, libtorch, onnxruntime, tvm and ncnn.
Ultralytics YOLOv5 in PyTorch for object detection, instance segmentation, classification, training, and export.
LiDAR R-CNN: An Efficient and Universal 3D Object Detector
A Simple and Versatile Framework for Object Detection and Instance Recognition
A treasure chest for visual classification and recognition powered by PaddlePaddle
PyTorch bottom-up attention with Detectron2
The pytorch re-implement of the official efficientdet with SOTA performance in real time and pretrained weights.