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awesome-adversarial-machine-learning

A curated list of awesome adversarial machine learning resources

brade31919.github.io

cedl_policy_gradient

cv_homework1

dcgan-tensorflow

A tensorflow implementation of Deep Convolutional Generative Adversarial Networks

deeplearning-500-questions

深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为18个章节，近30万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作，联系[email protected] 版权所有，违权必究 Tan 2018.06

depth-semantic-fully-conv

PyTorch Implementation for CS231N Course Project - "Fully Convolutional Network for Depth Estimation and Semantic Segmentation"

depth_360

Go Go ! For ICCV

dsplab_image_rotation

ee240500

featurelearning

FeatureLearning-ECCV2016

funcflow

Unsupervised Cosegmentation and Optical Flow fields using functional maps

ganhacks

starter from "How to Train a GAN?" at NIPS2016

homework0

homework2

homework3-1

homework5

imagejointunderstanding

kunena-forum

Kunena Forum - Forum / Bulletin Board / Discussions component for Joomla - This is the 5.x main development branch. Please do not open issues regarding earlier versions of Kunena

mnc

Instance-aware Semantic Segmentation via Multi-task Network Cascades

models

Models built with TensorFlow

monodepth-fpn-pytorch

Single Image Depth Estimation with Feature Pyramid Network

py-r-fcn

R-FCN with joint training and python support

radar_depth

Source code of the IROS 2020 paper "Depth Estimation from Monocular Images and Sparse Radar Data"

scalabel

Human-machine collaboration platform for visual data annotation

sequential-minimal-optimization

This is a Matlab implementation of SMO based on the original work from JC Platt

spherenet-pytorch

srgan-tensorflow

Tensorflow implementation of the SRGAN algorithm for single image super-resolution

superpoint

Efficient neural feature detector and descriptor

superpointpretrainednetwork

PyTorch pre-trained model for real-time interest point detection, description, and sparse tracking (https://arxiv.org/abs/1712.07629)