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

This repo includes the source code of the fully convolutional depth denoising model presented in https://arxiv.org/pdf/1909.01193.pdf (ICCV19)

The Official PyTorch implementation of "3D Human Action Representation Learning via Cross-View Consistency Pursuit" in CVPR 2021

Repository for the paper "Extending Maps with Semantic and Contextual Object Information for Robot Navigation: a Learning-Based Framework using Visual and Depth Cues"

Code for Deep Surface Normal Estimation with Hierarchical RGB-D Fusion (CVPR2019)

Visualize Data From Stray Scanner https://keke.dev/blog/2021/03/10/Stray-Scanner.html

Applying Open3D functions to integrate experimentally measured color and depth frames into a 3D object.

3D pose estimation of an RGB-D camera using the least squares technique

Code for CVPR 2021 paper. "Calibrated RGB-D Salient Object detection".

Fast and robust upper body orientation estimation for mobile robotic applications

SLAM code for RGB-D images in python.

The Official PyTorch implementation of "Learning Multi-View Interactional Skeleton Graph for Action Recognition" in TPAMI 2020

[AAAI 2023 Oral] CoMAE: Single Model Hybrid Pre-training on Small-Scale RGB-D Datasets

This repository contains all the scripts used in the master thesis entitled " Autonmous Grabbing with RGB-D", in which an Intel Realsense D455 camera is used to enable a Kuka IIWA 14 robotic arm grab and track a suspended block with the help of ArUco markers

RGB-D Salient Object Detection with Ubiquitous Target Awareness. IEEE Transactions on Image Processing (TIP) 2021

[TIP 2022] official repo of "Weakly Supervised RGB-D Salient Object Detection with Prediction Consistency Training and Active Scribble Boosting"

RGB-D fusion for two-hand reconstruction

Code for NeurIPS 2021 paper. "Joint Semantic Mining for Weakly Supervised RGB-D Salient Object Detection".

This tool takes a mesh file as its input and outputs an RGB image and a depth image.

A project for computing high-quality ground truth training examples for RGB-D data.