An extension of Open3D to address 3D Machine Learning tasks

Python code to fuse multiple RGB-D images into a TSDF voxel volume.

DN-Splatter + AGS-Mesh: Depth and Normal Priors for Gaussian Splatting

A multi-sensor capture system for free viewpoint video.

[ECCV 2020] PyTorch Implementation of some RGBD Semantic Segmentation models.

[TPAMI 2023, 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

ESANet: Efficient RGB-D Semantic Segmentation for Indoor Scene Analysis

3D Graph Neural Networks for RGBD Semantic Segmentation

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]

Dataset and Code for the paper "DepthTrack: Unveiling the Power of RGBD Tracking" (ICCV2021), and "Depth-only Object Tracking" (BMVC2021)

Collection of scripts for generating depth maps for videos using machine learning.

Python implementation of RGBD-PTAM algorithm

TriDepth: Triangular Patch-based Deep Depth Prediction [Kaneko+, ICCVW2019(oral)]

EMSANet: Efficient Multi-Task RGB-D Scene Analysis for Indoor Environments

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)