learning-topology-synthetic-data
STEPS
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| learning-topology-synthetic-data | STEPS | |
|---|---|---|
| 5 | 1 | |
| 37 | 165 | |
| - | - | |
| 4.3 | 10.0 | |
| 9 months ago | about 1 year ago | |
| Python | Python | |
| GNU General Public License v3.0 or later | MIT License |
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learning-topology-synthetic-data
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Want to use synthetic data, but don't want to deal with domain gap?
For those interested, here are our source code with pretrained mdoels (it is light-weight so it runs on your local machine!) and arxiv version of our paper.
paper: https://arxiv.org/pdf/2106.02994.pdf
Here are some of the reconstructions produced by our method:
https://github.com/alexklwong/learning-topology-synthetic-da...
https://github.com/alexklwong/learning-topology-synthetic-da...
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[N][R] Want to leverage synthetic data for 3d reconstruction, but don't want to deal with the photometric domain gap? (ICRA 2021 talk)
Code for https://arxiv.org/abs/2106.02994 found: https://github.com/alexklwong/learning-topology-synthetic-data
STEPS
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Meet STEPS: A New Computer Vision Method That Jointly Learns A Nighttime Image Enhancer And A Depth Estimator Without Using Ground Truth
Quick Read: https://www.marktechpost.com/2023/02/07/meet-steps-a-new-computer-vision-method-that-jointly-learns-a-nighttime-image-enhancer-and-a-depth-estimator-without-using-ground-truth/ Paper: https://arxiv.org/pdf/2302.01334v1.pdf Github: https://github.com/ucaszyp/STEPS
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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)
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