OpenMMLab's next-generation platform for general 3D object detection.
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Updated
Feb 14, 2023 - Python
OpenMMLab's next-generation platform for general 3D object detection.
A general 3D object detection codebse.
The Medical Detection Toolkit contains 2D + 3D implementations of prevalent object detectors such as Mask R-CNN, Retina Net, Retina U-Net, as well as a training and inference framework focused on dealing with medical images.
An extension of Open3D to address 3D Machine Learning tasks
The PyTorch Implementation based on YOLOv4 of the paper: "Complex-YOLO: Real-time 3D Object Detection on Point Clouds"
[CVPR 2022 Oral, Best Student Paper] EPro-PnP: Generalized End-to-End Probabilistic Perspective-n-Points for Monocular Object Pose Estimation
KITTI Object Visualization (Birdview, Volumetric LiDar point cloud )
alfred-py: A deep learning utility library for **human**, more detail about the usage of lib to: https://zhuanlan.zhihu.com/p/341446046
Super Fast and Accurate 3D Object Detection based on 3D LiDAR Point Clouds (The PyTorch implementation)
Paper reading notes on Deep Learning and Machine Learning
SMOKE: Single-Stage Monocular 3D Object Detection via Keypoint Estimation
3D Bounding Box Annotation Tool (3D-BAT) Point cloud and Image Labeling
Codes for “Fully Sparse 3D Object Detection” & “Embracing Single Stride 3D Object Detector with Sparse Transformer”
The official PyTorch Implementation of RTM3D and KM3D for Monocular 3D Object Detection
CIA-SSD: Confident IoU-Aware Single Stage Object Detector From Point Cloud, AAAI 2021.
nnDetection is a self-configuring framework for 3D (volumetric) medical object detection which can be applied to new data sets without manual intervention. It includes guides for 12 data sets that were used to develop and evaluate the performance of the proposed method.
A 3D vision library from 2D keypoints: monocular and stereo 3D detection for humans, social distancing, and body orientation.
A lightweight tool for labeling 3D bounding boxes in point clouds.
Papers on 3D Object Detection for Autonomous Driving
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