student-teacher-anomaly-detection
learning-topology-synthetic-data
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| student-teacher-anomaly-detection | learning-topology-synthetic-data | |
|---|---|---|
| 1 | 5 | |
| 113 | 25 | |
| - | - | |
| 0.4 | 2.8 | |
| 7 months ago | 8 months ago | |
| Python | Python | |
| - | GNU General Public License v3.0 or later |
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student-teacher-anomaly-detection
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[R] Introduction to Fast Dense Feature Extraction -- A fast way to extract visual features for many patches from an image
Code for https://arxiv.org/abs/1911.02357 found: https://github.com/denguir/student-teacher-anomaly-detection
learning-topology-synthetic-data
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Want to use synthetic data, but don't want to deal with domain gap?
https://github.com/alexklwong/learning-topology-synthetic-da...
Check out the extended version of our ICRA 2021 talk for Learning Topology from Synthetic Data for Unsupervised Depth Completion:
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
TLDR: Here is a gif showing an overview of our approach
What are some alternatives?
DETReg - Official implementation of the CVPR 2022 paper "DETReg: Unsupervised Pretraining with Region Priors for Object Detection".
image-quality-assessment - Convolutional Neural Networks to predict the aesthetic and technical quality of images.
protein-bert-pytorch - Implementation of ProteinBERT in Pytorch
HyperGAN - Composable GAN framework with api and user interface
d2l-en - Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 300 universities from 55 countries including Stanford, MIT, Harvard, and Cambridge.
Fast_Dense_Feature_Extraction - A Pytorch and TF implementation of the paper "Fast Dense Feature Extraction with CNNs with Pooling Layers"
bpycv - Computer vision utils for Blender (generate instance annoatation, depth and 6D pose by one line code)
unsupervised-depth-completion-visual-inertial-odometry - Tensorflow implementation of Unsupervised Depth Completion from Visual Inertial Odometry (in RA-L January 2020 & ICRA 2020)