Awesome Directed Fuzzing Alternatives
A curated list of awesome directed fuzzing research papers
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Awesome Directed Fuzzing | 373 | a year ago | ||||||||
| A curated list of awesome directed fuzzing research papers | ||||||||||
| Msrn Pytorch | 188 | 4 years ago | 2 | mit | Python | |||||
| This repository is a PyTorch version of the paper "Multi-scale Residual Network for Image Super-Resolution" (ECCV 2018). | ||||||||||
| Awesome Database Testing | 158 | a year ago | gpl-3.0 | |||||||
| 数据库测试资料 This repo is a collection of resources on testing database systems | ||||||||||
| Mobilenet | 110 | 6 years ago | 2 | apache-2.0 | Python | |||||
| A Clearer and Simpler MobileNet Implementation in TensorFlow | ||||||||||
| Traclus_impl | 101 | 1 | 3 years ago | 27 | April 04, 2016 | 7 | Python | |||
| Python implementation of Traclus algorithm, for 2-D trajectories | ||||||||||
| Iclr2017mcnet | 88 | 6 years ago | 1 | mit | Python | |||||
| Tensorflow implementation of the ICLR 2017 paper: Decomposing Motion and Content for Natural Video Sequence Prediction | ||||||||||
| Ista Net Pytorch | 84 | 3 years ago | 3 | Python | ||||||
| ISTA-Net: Interpretable Optimization-Inspired Deep Network for Image Compressive Sensing, CVPR2018 (PyTorch Code) | ||||||||||
| Deepid Implementation | 73 | 9 years ago | 12 | Shell | ||||||
| DeepID-implementation is an implementation of paper "Deep Learning Face Representation from Predicting 10,000 Classes" | ||||||||||
| Gazefollowing | 72 | 4 years ago | mit | Python | ||||||
| Code for ACCV2018 paper 'Believe It or Not, We Know What You Are Looking at!' | ||||||||||
| Cgintrinsics | 66 | 4 years ago | 8 | mit | Python | |||||
| This is the CGIntrinsics implementation described in the paper "CGIntrinsics: Better Intrinsic Image Decomposition through Physically-Based Rendering, Z. Li and N. Snavely, ECCV 2018". | ||||||||||
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