Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
---|---|---|---|---|---|---|---|---|---|---|
Flatnet | 25 | 5 months ago | 4 | bsd-3-clause | Jupyter Notebook | |||||
This is the official pytorch code repo for the ICCV 2019 paper Towards Photorealistic Reconstruction of Highly Multiplexed Lensless Images and the TPAMI 2020 paper FlatNet: Towards Photorealistic Scene Reconstruction from Lensless Measurements | ||||||||||
Reconnet Pytorch | 10 | 3 years ago | mit | Jupyter Notebook | ||||||
A non-iterative algorithm to reconstruct images from compressively sensed measurements. | ||||||||||
Anthropometric Clothing Measurements From 3d Body Scans | 10 | 3 years ago | 2 | Jupyter Notebook | ||||||
Code and Datasets for Anthropometric clothing measurements from 3D body scans (MVA2020 paper) | ||||||||||
Ttmf | 8 | 5 years ago | 2 | Python | ||||||
TTMF: A Triple Trustworthiness Measurement Frame for Knowledge Graphs | ||||||||||
Blogforever Crawler Publication | 7 | 9 years ago | mit | TeX | ||||||
BlogForever Crawler publication | ||||||||||
Tmodel Ccs2018.github.io | 7 | 3 years ago | Python | |||||||
Privacy-Preserving Dynamic Learning of Tor Network Traffic | ||||||||||
Ssllandscape | 6 | 10 years ago | Python | |||||||
Source code for our paper: "The SSL Landscape - a thorough analysis of the X.509 PKI using active and passive measurements" | ||||||||||
Satellite_led_liverpool | 6 | 5 years ago | Jupyter Notebook | |||||||
Data and code for the paper "Remote Sensing-Based Measurement of Living Environment Deprivation - Improving Classical Approaches with Machine Learning", by Dani Arribas-Bel, Jorge Patiño and Juanca Duque | ||||||||||
Mcsm_tip2018 | 6 | 5 years ago | Lua | |||||||
Source code of our TIP 2018 paper "Modality-specific Cross-modal Similarity Measurement with Recurrent Attention Network". | ||||||||||
Networked Popularity | 5 | 4 years ago | mit | Python | ||||||
Code and Data for paper: Estimating Attention Flow in Online Video Networks (CSCW '19) |