Open-source alternatives to Pointconv

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

Paper: Feedback Networks, CVPR 2017.

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.

Refign: Align and Refine for Adaptation of Semantic Segmentation to Adverse Conditions WACV 2023

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.

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"

CVPR 2021 & IJCV 2024 Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers

Created by Charles R. Qi , Wei Liu , Chenxia Wu , Hao Su and Leonidas J. Guibas from Stanford University and Nuro Inc.

Unsupervised Intra-domain Adaptation for Semantic Segmentation through Self-Supervision (CVPR 2020 Oral)

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,…

Implementation for PolarNet: An Improved Grid Representation for Online LiDAR Point Clouds Semantic Segmentation (CVPR 2020)

Volumetric CNN (Convolutional Neural Networks) for Object Classification on 3D Data, with Torch implementation.

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

Shape Projective Fully Convolutional Network

Pytorch Implementation for NeurIPS (oral) paper: Pixel Level Cycle Association: A New Perspective for Domain Adaptive Semantic Segmentation

TPAMI 2023 ESI Highly Cited Paper SePiCo: Semantic-Guided Pixel Contrast for Domain Adaptive Semantic Segmentation https://arxiv.org/abs/2204.08808