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Code release for ConvNeXt V2 model
Python script for illustrating Convolutional Neural Networks (CNN) using Keras-like model definitions
Publication-ready NN-architecture schematics.
GUI for a Vocal Remover that uses Deep Neural Networks.
Escaping the Big Data Paradigm with Compact Transformers, 2021 (Train your Vision Transformers in 30 mins on CIFAR-10 with a single GPU!)
PyTorch Implementation of CvT: Introducing Convolutions to Vision Transformers
效果更好的补帧软件，显存占用更小，是DAIN速度的10-25倍，包含抽帧处理，去除动漫卡顿感
Sample code for Leopard USB3.0 Camera Linux Camera Tool
collection of super-resolution models & algorithms
Geometric Computer Vision Library for Spatial AI
Winning Solution in NTIRE19 Challenges on Video Restoration and Enhancement (CVPR19 Workshops) - Video Restoration with Enhanced Deformable Convolutional Networks. EDVR has been merged into BasicSR…
Open Source Image and Video Restoration Toolbox for Super-resolution, Denoise, Deblurring, etc. Currently, it includes EDSR, RCAN, SRResNet, SRGAN, ESRGAN, EDVR, BasicVSR, SwinIR, ECBSR, etc. Also …
Python implementation of MatLab imresize function
[CVPR 2019] Learning Parallax Attention for Stereo Image Super-Resolution
[CVPRW 2021] Symmetric Parallax Attention for Stereo Image Super-Resolution
OpenMMLab Pose Estimation Toolbox and Benchmark.
Variational autoencoder implemented in tensorflow and pytorch (including inverse autoregressive flow)
PyTorch implementation of Expected Patch Log Likelihood (EPLL) image prior in paper "D. Zoran and Y. Weiss, "From learning models of natural image patches to whole image restoration," ICCV 2011.
Roadmap to becoming an Artificial Intelligence Expert in 2022
One-paper-one-short-contribution-summary of all latest image/burst/video Denoising papers with code & citation published in top conference and journal.
Reimplement of 'Burst Denoising with Kernel Prediction Networks' and 'Multi-Kernel Prediction Networks for Denoising of Image Burst' by using PyTorch
a reimplementation of PWC-Net in PyTorch that matches the official Caffe version
Learning to See in the Dark in PyTorch