void-dataset
DAD-3DHeads
| void-dataset | DAD-3DHeads | |
|---|---|---|
| 3 | 1 | |
| 103 | 415 | |
| - | 1.4% | |
| 0.0 | 0.8 | |
| almost 2 years ago | about 1 year ago | |
| Shell | Python | |
| GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
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void-dataset
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Unsupervised Depth Completion from Visual Inertial Odometry
Hey there, interested in camera and range sensor fusion for point cloud (depth) completion?
Here is an extended version of our [talk](https://www.youtube.com/watch?v=oBCKO4TH5y0) at ICRA 2020 where we do a step by step walkthrough of our paper Unsupervised Depth Completion from Visual Inertial Odometry (joint work with Fei Xiaohan, Stephanie Tsuei, and Stefano Soatto).
In this talk, we present an unsupervised method (no need for human supervision/annotations) for learning to recover dense point clouds from images, captured by cameras, and sparse point clouds, produced by lidar or tracked by visual inertial odometry (VIO) systems. To illustrate what I mean, here is an [example](https://github.com/alexklwong/unsupervised-depth-completion-visual-inertial-odometry/blob/master/figures/void_teaser.gif?raw=true) of the point clouds produced by our method.
Our method is light-weight (so you can run it on your computer!) and is built on top of [XIVO] (https://github.com/ucla-vision/xivo) our VIO system.
For those interested here are links to the [paper](https://arxiv.org/pdf/1905.08616.pdf), [code](https://github.com/alexklwong/unsupervised-depth-completion-visual-inertial-odometry) and the [dataset](https://github.com/alexklwong/void-dataset) we collected.
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[N][R] ICRA 2020 extended talk for Unsupervised Depth Completion from Visual Inertial Odometry
Code for https://arxiv.org/abs/1905.08616 found: https://github.com/alexklwong/void-dataset
DAD-3DHeads
What are some alternatives?
unsupervised-depth-completion-visual-inertial-odometry - Tensorflow and PyTorch implementation of Unsupervised Depth Completion from Visual Inertial Odometry (in RA-L January 2020 & ICRA 2020)
transfiner - Mask Transfiner for High-Quality Instance Segmentation, CVPR 2022
xivo - X Inertial-aided Visual Odometry
3DDFA_V2 - The official PyTorch implementation of Towards Fast, Accurate and Stable 3D Dense Face Alignment, ECCV 2020.
instant-ngp - Instant neural graphics primitives: lightning fast NeRF and more
MICA - MICA - Towards Metrical Reconstruction of Human Faces [ECCV2022]
learning-topology-synthetic-data - Tensorflow implementation of Learning Topology from Synthetic Data for Unsupervised Depth Completion (RAL 2021 & ICRA 2021)
MonoScene - [CVPR 2022] "MonoScene: Monocular 3D Semantic Scene Completion": 3D Semantic Occupancy Prediction from a single image
3DDFA - The PyTorch improved version of TPAMI 2017 paper: Face Alignment in Full Pose Range: A 3D Total Solution.
6DRepNet - Official Pytorch implementation of 6DRepNet: 6D Rotation representation for unconstrained head pose estimation.
zozo-shift15m - SHIFT15M: Fashion-specific dataset for set-to-set matching with several distribution shifts