30 open-source projects similar to trucleduc/pointgrid, ranked by how many features they have in common. Compare stars, activity and what each one does to find the best PointGrid alternative.
PointNet is a deep learning architecture designed to process and classify raw 3D point clouds directly without voxelization. It provides a system for 3D object classification, semantic segmentation frameworks for partitioning clouds into categories, and tools for visualizing 3D shapes. The project utilizes a transform network to align point clouds into a canonical coordinate space and employs symmetric-function-based aggregation to condense point-wise features into global vectors regardless of point order. It also features a multi-scale grouping architecture to extract hierarchical geometric
PointNet++ is a deep learning framework designed for processing and classifying 3D point cloud data. It utilizes a hierarchical feature learning architecture to extract geometric patterns from sampled 3D point sets. The framework implements a variety of 3D analysis tools, including a point cloud classifier for categorizing objects based on spatial coordinates and surface normals, a semantic scene segmenter for labeling surfaces in large-scale environments, and a tool for 3D object part segmentation. The system covers a broad range of capabilities including geometric feature extraction, 3D da
SpiderCNN: Deep Learning on Point Sets with Parameterized Convolutional Filters. ECCV 2018 Yifan Xu, Tianqi Fan, Mingye Xu, Long Zeng, Yu Qiao.
PointConv: Deep Convolutional Networks on 3D Point Clouds. CVPR 2019 Wenxuan Wu, Zhongang Qi, Li Fuxin.
1st to MICCAI DigestPath2019 challenge (https://digestpath2019.grand-challenge.org/Home/) on colonoscopy tissue segmentation and classification task. (MICCAI 2019) https://teacher.bupt.edu.cn/zhuchuang/en/index.htm
IAST: Instance Adaptive Self-training for Unsupervised Domain Adaptation (ECCV 2020) https://teacher.bupt.edu.cn/zhuchuang/en/index.htm
Properties of dilated convolution are discussed in our ICLR 2016 conference paper. This repository contains the network definitions and the trained models. You can use this code together with vanilla Caffe to segment images using the pre-trained models. If you want to train the models yourself,…
Refign: Align and Refine for Adaptation of Semantic Segmentation to Adverse Conditions WACV 2023
Official Implementation of PiPa: Pixel- and Patch-wise Self-supervised Learning for Domain Adaptative Semantic Segmentation
3D/Volumetric Convolutional Neural Networks with Theano+Lasagne.
Hey guys! Welcome to this repository of our paper 'Phase Consistent Ecological Domain Adaptation', which is accepted by CVPR 2020. First things first, here's a link to our paper. Make sure to read it and you will like it. Currently we are organizing the code and will make it public available…
Official implementation for our ECCV 2022 paper "DecoupleNet: Decoupled Network for Domain Adaptive Semantic Segmentation"
Unsupervised Intra-domain Adaptation for Semantic Segmentation through Self-Supervision (CVPR 2020 Oral)
Created by Charles R. Qi , Wei Liu , Chenxia Wu , Hao Su and Leonidas J. Guibas from Stanford University and Nuro Inc.
Implementation for PolarNet: An Improved Grid Representation for Online LiDAR Point Clouds Semantic Segmentation (CVPR 2020)
CVPR 2021 & IJCV 2024 Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers
Volumetric CNN (Convolutional Neural Networks) for Object Classification on 3D Data, with Torch implementation.
OctNet uses efficient space partitioning structures (i.e. octrees) to reduce memory and compute requirements of 3D convolutional neural networks, thereby enabling deep learning at high resolutions.
TPAMI 2023 ESI Highly Cited Paper SePiCo: Semantic-Guided Pixel Contrast for Domain Adaptive Semantic Segmentation https://arxiv.org/abs/2204.08808
TITAN-Net introduces a fresh, effective approach for bridging the gap between sensor modalities with different data formats! 🌉 By harnessing the power of scene semantics, TITAN-Net can, for the very first time, synthesize a panoramic color image directly from a 3D LiDAR point cloud.
Style-Hallucinated Dual Consistency Learning for Domain Generalized Semantic Segmentation. ECCV 2022
by Hengshuang Zhao, Jianping Shi, Xiaojuan Qi, Xiaogang Wang, Jiaya Jia, details are in project page.
DeconvNet : Learning Deconvolution Network for Semantic Segmentation
The code and trained models of: Affinity Space Adaptation for Semantic Segmentation Across Domains.
Created by Itai Lang, Asaf Manor, and Shai Avidan from Tel Aviv University.
Jun Fu, Jing Liu, Haijie Tian, Yong Li, Yongjun Bao, Zhiwei Fang,and Hanqing Lu
Voxel-Based Variational Autoencoders, VAE GUI, and Convnets for Classification