An extension of Open3D to address 3D Machine Learning tasks
-
Updated
Jun 2, 2024 - Python
An extension of Open3D to address 3D Machine Learning tasks
Python code to fuse multiple RGB-D images into a TSDF voxel volume.
A multi-sensor capture system for free viewpoint video.
[ECCV 2020] PyTorch Implementation of some RGBD Semantic Segmentation models.
[TPAMI 2022, NeurIPS 2020] Code release for "Deep Multimodal Fusion by Channel Exchanging"
OcclusionFusion: realtime dynamic 3D reconstruction based on single-view RGB-D
[ECCV-20] 3D human scene interaction dataset: https://people.eecs.berkeley.edu/~zhecao/hmp/index.html
3D Graph Neural Networks for RGBD Semantic Segmentation
ESANet: Efficient RGB-D Semantic Segmentation for Indoor Scene Analysis
This repo includes the source code of the fully convolutional depth denoising model presented in https://arxiv.org/pdf/1909.01193.pdf (ICCV19)
ShapeConv: Shape-aware Convolutional Layer for Indoor RGB-D Semantic Segmentation (ICCV 2021)
Code for ICCV 2019 paper. "Depth-induced Multi-scale Recurrent Attention Network for Saliency Detection". [RGB-D Salient Object Detection]
Python implementation of RGBD-PTAM algorithm
TriDepth: Triangular Patch-based Deep Depth Prediction [Kaneko+, ICCVW2019(oral)]
Applying Open3D functions to integrate experimentally measured color and depth frames into a 3D object.
Implement some state-of-the-art methods of Semantic Scene Completion (SSC) task in PyTorch. [1] 3D Sketch-aware Semantic Scene Completion via Semi-supervised Structure Prior (CVPR 2020)
EMSANet: Efficient Multi-Task RGB-D Scene Analysis for Indoor Environments
Add a description, image, and links to the rgbd topic page so that developers can more easily learn about it.
To associate your repository with the rgbd topic, visit your repo's landing page and select "manage topics."