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LIR-LIVO: A Lightweight,Robust Lidar/Vision/Inertial Odometry with Illumination-Resilient Deep Features
SegLocNet: Multimodal Localization Network for Autonomous Driving via Bird’s-Eye-View Segmentation
Efficient neural feature detector and descriptor
标注自己的数据集，训练、评估、测试、部署自己的人工智能算法
Code for "Efficient LoFTR: Semi-Dense Local Feature Matching with Sparse-Like Speed", CVPR 2024
This is the official code base of VectorMapNet (ICML 2023)
Monocular Lane Detection Based on Deep Learning: A Survey
LLM Frontend for Power Users.
Transformer: PyTorch Implementation of "Attention Is All You Need"
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
End-to-End Object Detection with Transformers
[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.
[ICRA'23] BEVFusion: Multi-Task Multi-Sensor Fusion with Unified Bird's-Eye View Representation
[ICLR'23 Spotlight & ECCV'24 & IJCV'24] MapTR: Structured Modeling and Learning for Online Vectorized HD Map Construction
A general map auto annotation framework based on MapTR, with high flexibility in terms of spatial scale and element type
PyTorch implementation of the U-Net for image semantic segmentation with high quality images
Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.
Source Code for Paper "OrienterNet Visual Localization in 2D Public Maps with Neural Matching"
Datasets, Transforms and Models specific to Computer Vision
《动手学深度学习》：面向中文读者、能运行、可讨论。中英文版被70多个国家的500多所大学用于教学。
本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为PyTorch实现。
A computationally efficient and robust LiDAR-inertial odometry (LIO) package
An efficient single/multi-agent trajectory planner for multicopters.
"Visual-Inertial Dataset" (RA-L'21 with ICRA'21): it contains harsh motions for VO/VIO, like pure rotation or fast rotation with various motion types.
[CMU] A Versatile and Modular Framework Designed for Autonomous Unmanned Aerial Vehicles [UAVs] (C++/ROS/PX4)