Learning_by_association
This repository contains code for the paper Learning by Association - A versatile semi-supervised training method for neural networks (CVPR 2017) and the follow-up work Associative Domain Adaptation (ICCV 2017).
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
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| A list of papers, docs, codes about model quantization. This repo is aimed to provide the info for model quantization research, we are continuously improving the project. Welcome to PR the works (papers, repositories) that are missed by the repo. | ||||||||||
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| Relation-Shape Convolutional Neural Network for Point Cloud Analysis (CVPR 2019 Oral & Best paper finalist) | ||||||||||
| Cnn_face_detection | 250 | 7 years ago | 9 | Python | ||||||
| Implementation based on the paper Li et al., “A Convolutional Neural Network Cascade for Face Detection, ” 2015 CVPR | ||||||||||
| Learning_to_sample | 160 | 10 months ago | other | Python | ||||||
| A learned sampling approach for point clouds (CVPR 2019) | ||||||||||
| Fooling | 154 | 7 years ago | 5 | C++ | ||||||
| Code base for "Deep Neural Networks are Easily Fooled" CVPR 2015 paper | ||||||||||
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