ICRA 2018 "Sparse-to-Dense: Depth Prediction from Sparse Depth Samples and a Single Image" (Torch Implementation)
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Updated
Jul 21, 2018 - Lua
ICRA 2018 "Sparse-to-Dense: Depth Prediction from Sparse Depth Samples and a Single Image" (Torch Implementation)
NIPS 2018 "Invertibility of Convolutional Generative Networks from Partial Measurements"
ICRA 2018 "Sparse-to-Dense: Depth Prediction from Sparse Depth Samples and a Single Image" (PyTorch Implementation)
Nearest neighbor depth completion
My academic research project on depth completion for LIDAR sequences at the University of Queensland
Unofficial Faster PyTorch implementation of Convolutional Spatial Propagation Network
A real-time depth filling approach based on prior image segmentation (http://www.atapour.co.uk/papers/BMVC2017.pdf).
LiDAR Guided Boundary Bleeding Refinement for Depth Map
Leveraging GradSLAM Multi-view gradients to optimize RGB-D Images: Experiments and Insights
2D/ 3D object detection, segmentation, depth estimation for self-driving car
NeurIPS 2019: Deep RGB-D Canonical Correlation Analysis For Sparse Depth Completion
ICRA 2019 "Self-supervised Sparse-to-Dense: Self-supervised Depth Completion from LiDAR and Monocular Camera"
ICRA 2021 "Towards Precise and Efficient Image Guided Depth Completion"
PyTorch implementation of An Adaptive Framework for Learning Unsupervised Depth Completion (RAL 2021 & ICRA 2021)
This is an official implementation of "DEN: Disentangling and Exchanging Network for Depth Completion" in TensorFlow.
Online 3D modeling by depth completion (RA-L 2021)
Python script for performing depth completion from sparse depth and rgb images using the msg_chn_wacv20. model in ONNX
Python script for performing depth completion from sparse depth and rgb images using the msg_chn_wacv20. model in Tensorflow Lite.
Implementation of our paper entitiled LiDAR-ToF-Binocular depth fusion using gradient priors published in CCDC.
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