Open-source alternatives to DSGN

0. The CUDA and Pytorch version that is used for this work: ~~~ 'CUDA==10.0', 'torch==1.1.0', 'CUDNN==7.5.0' ~~~ Warning: We tried CUDA11.0+Torch1.7.1 on RTX3090, the AP performance is significantly lower than the aforementioned environment setup.

This repository is for the ICCV 2021 paper NEAT: Neural Attention Fields for End-to-End Autonomous Driving.

By Prarthana Bhattacharyya, Chengjie Huang and Krzysztof Czarnecki.

RTM3D(ECCV2020) and KM3D (namely RTM3D++) are efficiency and accuracy monocular 3D object detection methods for autonomous driving.

Accepted to CVPR2023. 🔥

This is a release of the code of our paper Back-tracing Representative Points for Voting-based 3D Object Detection in Point Clouds, CVPR 2021.

Code release for the paper ST3D: Self-training for Unsupervised Domain Adaptation on 3D Object Detection, CVPR 2021 and ST3D++: Denoised Self-training for Unsupervised Domain Adaptation on 3D Object Detection, T-PAMI 2022.

Mingyu Ding, Yuqi Huo, Hongwei Yi, Zhe Wang, Jianping Shi, Zhiwu Lu, Ping Luo

Pytorch implementation of Depth-conditioned Dynamic Message Propagation forMonocular 3D Object Detection, a paper on CVPR2021.

Garrick Brazil, Xiaoming Liu

:pointright::pointright::pointright:This repo is permanently moved to https://github.com/Ghostish/Open3DSOT :pointleft::pointleft::pointleft:

Instance Segmentation in 3D Scenes using Semantic Superpoint Tree Networks(ICCV2021) by Zhihao Liang, Zhihao Li, Songcen Xu, Mingkui Tan, Kui Jia. (\) Corresponding author. [arxiv](https://arxiv.org/abs/2108.07478)…

This is the official repo of 'Weakly Supervised 3D object detection from Lidar Point Cloud' (ECCV2020). Author: Qinghao Meng, Wenguan Wang, Tianfei Zhou, Jianbing Shen, Luc Van Gool, and Dengxin Dai

Hierarchical Aggregation for 3D Instance Segmentation ICCV 2021

Created by Zeyu HU

This is a reproduced repo of "From Voxel to Point: IoU-guided 3D Object Detection for Point Cloud with Voxel-to-Point Decoder" (FromVoxelToPoint) and "Anchor-free 3D Single Stage Detector with Mask-Guided Attention for Point Cloud" (MGAF-3DSSD) in ACM MM 2021.

Jonas Schult 1 , Francis Engelmann 2,3 , Alexander Hermans 1 , Or Litany 4 , Siyu Tang 3 , Bastian Leibe 1

The official implementation of Rank & Sort Loss. Our implementation is based on mmdetection.

In depth-sensing applications ranging from home robotics to AR/VR, it will be common to acquire 3D scans of interior spaces repeatedly at sparse time intervals (e.g., as part of regular daily use). We propose an algorithm that analyzes these ``rescans'' to infer a temporal model of a scene with…

27/04/2023

ECCV 2022 (Oral Presentation)

This repository contains the implementation of CenterFusion: Center-based Radar and Camera Fusion for 3D Object Detection.

This repository is the official PyTorch implementation of Active Learning for Deep Object Detection via Probabilistic Modeling, ICCV 2021.

OpenPCDet is a PyTorch deep learning library and toolbox for LiDAR 3D object detection. It functions as a point cloud processing framework designed to develop, train, and evaluate machine learning models that identify and locate objects in three dimensional space. The project includes a GPU-accelerated geometry engine for high-performance implementation of 3D intersection over union and rotated non-maximum suppression. It also provides a distributed model training tool to scale the training and testing of detection models across multiple GPUs and computing nodes. The framework covers point c

World's first general purpose 3D object detection codebse.

Canonical Voting: Towards Robust Oriented Bounding Box Detection in 3D Scenes