student-teacher-anomaly-detection VS learning-topology-synthetic-data

Compare student-teacher-anomaly-detection vs learning-topology-synthetic-data and see what are their differences.

Our great sponsors
  • SonarQube - Static code analysis for 29 languages.
  • Scout APM - Less time debugging, more time building
  • SaaSHub - Software Alternatives and Reviews
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
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

student-teacher-anomaly-detection

Posts with mentions or reviews of student-teacher-anomaly-detection. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-07-31.

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.

What are some alternatives?

When comparing student-teacher-anomaly-detection and learning-topology-synthetic-data you can also consider the following projects:

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)