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Gorilla-Lab-SCUT avatar

Gorilla-Lab-SCUT/SSTNet

0
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114 stars·9 forks·Python·MIT·0 views

SSTNet

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]…

Features

  • 3D Detection and Segmentation - Instance segmentation using semantic superpoint tree networks.

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Open-source alternatives to SSTNet

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Frequently asked questions

What does gorilla-lab-scut/sstnet do?

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)…

What are the main features of gorilla-lab-scut/sstnet?

The main features of gorilla-lab-scut/sstnet are: 3D Detection and Segmentation.

What are some open-source alternatives to gorilla-lab-scut/sstnet?

Open-source alternatives to gorilla-lab-scut/sstnet include: yanx27/pointnet_pointnet2_pytorch — This project is a PyTorch-based framework of deep learning models designed for the classification and semantic… intel-isl/open3d — Open3D is a 3D data processing library, visualization engine, and machine learning library. It provides a framework… aim-uofa/dyco3d — Code for the paper DyCo3D: Robust Instance Segmentation of 3D Point Clouds through Dynamic Convolution, CVPR 2021. anonymous0522/raan — 0. The CUDA and Pytorch version that is used for this work: ~~~ 'CUDA==10.0', 'torch==1.1.0', 'CUDNN==7.5.0' ~~~… autonomousvision/neat — This repository is for the ICCV 2021 paper NEAT: Neural Attention Fields for End-to-End Autonomous Driving. angeladai/3dmv — 3DMV jointly combines RGB color and geometric information to perform 3D semantic segmentation of RGB-D scans. This…