learning-topology-synthetic-data VS void-dataset

Compare learning-topology-synthetic-data vs void-dataset and see what are their differences.

learning-topology-synthetic-data

Tensorflow implementation of Learning Topology from Synthetic Data for Unsupervised Depth Completion (RAL 2021 & ICRA 2021) (by alexklwong)
Machine Learning Computer Vision Deep Learning Tensorflow depth depth-estimation depth-completion unsupervised-learning sensor-fusion 3d-vision 3d-reconstruction kitti Void self-supervised-learning Ral icra ucla
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void-dataset

Visual Odometry with Inertial and Depth (VOID) dataset (by alexklwong)
Computer Vision Machine Learning depth-completion sparse-to-dense Dataset 3d-vision icra Ral 3d-reconstruction
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learning-topology-synthetic-data void-dataset
5 3
37 103
- -
4.3 0.0
9 months ago almost 2 years ago
Python Shell
GNU General Public License v3.0 or later GNU General Public License v3.0 or later
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learning-topology-synthetic-data

Posts with mentions or reviews of learning-topology-synthetic-data. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-09-24.

void-dataset

Posts with mentions or reviews of void-dataset. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-08-30.
  • Unsupervised Depth Completion from Visual Inertial Odometry
    3 projects | news.ycombinator.com | 30 Aug 2021
    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.

  • [N][R] ICRA 2020 extended talk for Unsupervised Depth Completion from Visual Inertial Odometry
    4 projects | /r/MachineLearning | 30 Aug 2021
    Code for https://arxiv.org/abs/1905.08616 found: https://github.com/alexklwong/void-dataset

What are some alternatives?

When comparing learning-topology-synthetic-data and void-dataset you can also consider the following projects:

d2l-en - Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.

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)

bpycv - Computer vision utils for Blender (generate instance annoatation, depth and 6D pose by one line code)

instant-ngp - Instant neural graphics primitives: lightning fast NeRF and more

student-teacher-anomaly-detection - Student–Teacher Anomaly Detection with Discriminative Latent Embeddings

xivo - X Inertial-aided Visual Odometry

DECA - DECA: Detailed Expression Capture and Animation (SIGGRAPH 2021)

DAD-3DHeads - Official repo for DAD-3DHeads: A Large-scale Dense, Accurate and Diverse Dataset for 3D Head Alignment from a Single Image (CVPR 2022).

Make-It-3D - [ICCV 2023] Make-It-3D: High-Fidelity 3D Creation from A Single Image with Diffusion Prior

NeuralRecon - Code for "NeuralRecon: Real-Time Coherent 3D Reconstruction from Monocular Video", CVPR 2021 oral

STEPS - This is the official repository for ICRA-2023 paper "STEPS: Joint Self-supervised Nighttime Image Enhancement and Depth Estimation"

learning-topology-synthetic-data vs d2l-en void-dataset vs unsupervised-depth-completion-visual-inertial-odometry learning-topology-synthetic-data vs bpycv void-dataset vs instant-ngp learning-topology-synthetic-data vs student-teacher-anomaly-detection void-dataset vs xivo learning-topology-synthetic-data vs DECA void-dataset vs DAD-3DHeads learning-topology-synthetic-data vs unsupervised-depth-completion-visual-inertial-odometry learning-topology-synthetic-data vs Make-It-3D learning-topology-synthetic-data vs NeuralRecon learning-topology-synthetic-data vs STEPS