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advdefense_csc

Code for "Adversarial Defense by Stratified Convolutional Sparse Coding"

awesome-face_recognition

papers about Face Detection; Face Alignment; Face Recognition && Face Identification && Face Verification && Face Representation; Face Reconstruction; Face Tracking; Face Super-Resolution && Face Deblurring; Face Generation && Face Synthesis; Face Transfer; Face Anti-Spoofing; Face Retrieval;

bingbike_beta

bingbike_server

cagface

Component Attention Guided Face Super-Resolution Network: CAGFace

ccsc_code_iccv2017

This is the source code repository for the ICCV 2017 paper "Consensus Convolutional Sparse Coding".

convsparsecoding

Code accompanying the paper M. Sorel, F. Sroubek, "Fast convolutional sparse coding using matrix inversion lemma", Digital Signal Processing, vol. 55, pp.44-51, 2016

deep-convolution-network-for-direction-of-arrival-estimation-with-sparse-prior

this code is for the paper 'Deep Convolution Network for Direction of Arrival Estimation with Sparse Prior' pubished in IEEE spl

face-hallucination-for-video-surveillance-graduation-project-

a novel face hallucination algorithm to synthesize a high-resolution face image from several low-resolution input face images. Face hallucination normally uses twomodels: a global parametricmodel which synthesizes the global face shapes from eigenfaces, and a local parametric model which enhances the local high frequency details.We follow a similar process to develop a robust face hallucination algorithm. First, we obtain eigenfaces from a number of low resolution face images segmented from a video sequence using a face tracking algorithm. Then we compute the difference between an interpolated low-resolution face and a mean face, and use this difference as the query to retrieve an approximate sparse eigenface representation. The eigenfaces are combined using the coefficients obtained from the sparse representation and added into the interpolated low-resolution face. In this way, the global shape of the interpolated low resolution face can be successfully enhanced. Second, we improve the example-based super-resolution method for local high frequency information enhancement. Our proposed algorithm uses the Approximate Nearest Neighbors (ANN) search method to find a number of nearest neighbors for a stack of queries, instead of finding the exact match for each low frequency patch. Median filtering is used to remove the noise from the nearest neighbors in order to enhance the signal. Our proposed algorithm uses a sparse representation and the ANN method to enhance both global face shape and local high frequency information while greatly improving the processing speed, as confirmed empirically.

face-recognition

Identify low-resolution video face images; contain main three sections: face detection,low resolution face super resolution; face recognition.

faceattr

CVPR2018 Face Super-resolution with supplementary Attributes

fcsc

An implementation of Bristow et al.'s CVPR 2013 paper "Fast Convolutional Sparse Coding".

fsrnet

Demo code for our CVPR'18 paper "FSRNet: End-to-End Learning Face Super-Resolution with Facial Priors" (SPOTLIGHT Presentation)

gwainet

Exemplar Guided Face Image Super-Resolution without Facial Landmarks

image-super-resolution

🔎 Super-scale your images and run experiments with Residual Dense and Adversarial Networks.

image_sr

lw-csc

Image Super-Resolution by Learning Weighted Convolutional Sparse Coding

ms-csc-rain-streak-removal

There is a code of ”Video Rain Streak Removal By Multiscale Convolutional Sparse Coding”　ｉｎ. There are several added comparison results in different real videos to further show the superiority of the MS-CSC model.

ocsc

Code for 'Online convolutional sparse coding'.

progressive-face-super-resolution

Official Pytorch Implementation of Progressive Face Super-Resolution (BMVC 2019 Accepted)

pwls-cscgr

Convolutional Sparse Coding for Compressed Sensing CT Reconstruction

single-image-super-resolution

A collection of high-impact and state-of-the-art SR methods

stacked-gan-face-sr

Stacked GAN face super resolution

super-resolution-networks

Using different sr networks to reconstruct small face images

ta_frontend

The front-end of my final tasks : Single Image Super Resolution for Face Images using Generative Adversarial Network

ta_server

The back-end of my final tasks : Single Image Super Resolution for Face Images using Generative Adversarial Network

waveletsrnet

A pytorch implementation of Paper "Wavelet-srnet: A wavelet-based cnn for multi-scale face super resolution"