The code of 'Towards Domain-agnostic depth completion'
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Updated
Aug 4, 2022
The code of 'Towards Domain-agnostic depth completion'
My academic research project on depth completion for LIDAR sequences at the University of Queensland
Python script for performing depth completion from sparse depth and rgb images using the msg_chn_wacv20. model in Tensorflow Lite.
ECCV24 Official Code for Depth on Demand: Streaming Dense Depth from a Low Frame-Rate Active Sensor
CVPR 2024: Robust Depth Enhancement via Polarization Prompt Fusion Tuning
Implementation of our paper entitiled S&CNet: A lightweight network for fast and accurate depth completion published in JVCI.
Implementation of our paper entitiled LiDAR-ToF-Binocular depth fusion using gradient priors published in CCDC.
Leveraging GradSLAM Multi-view gradients to optimize RGB-D Images: Experiments and Insights
PyTorch implementation of An Adaptive Framework for Learning Unsupervised Depth Completion (RAL 2021 & ICRA 2021)
2D/ 3D object detection, segmentation, depth estimation for self-driving car
Python script for performing depth completion from sparse depth and rgb images using the msg_chn_wacv20. model in ONNX
[TPAMI 23‘] ActiveZero++: Mixed Domain Learning Stereo and Confidence-based Depth Completion with Zero Annotation
Depth Completion technique agnostic to input depth pattern sparsity, WACV23
Attentive Bilateral Convolutional Network for Robust Depth Completion
Online 3D modeling by depth completion (RA-L 2021)
Supervised Depth Completion of RGB-D Measurements from Reconstruction Loss
NIPS 2018 "Invertibility of Convolutional Generative Networks from Partial Measurements"
This is an official implementation of "DEN: Disentangling and Exchanging Network for Depth Completion" in TensorFlow.
ICASSP 2021: Scene Completeness-Aware Lidar Depth Completion for Driving Scenario
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