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ccyzf's starred repositories

SimSwap

An arbitrary face-swapping framework on images and videos with one single trained model!

Language:PythonNOASSERTION434800

latent-pose-reenactment

The authors' implementation of the "Neural Head Reenactment with Latent Pose Descriptors" (CVPR 2020) paper.

Language:PythonApache-2.017900

head2head

PyTorch implementation for Head2Head and Head2Head++. It can be used to fully transfer the head pose, facial expression and eye movements from a source video to a target identity.

Language:PythonMIT30700

lsct_phiqnet

LSCT-PHIQNet

Language:PythonMIT1200

voice_conversion

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MockingBird

🚀AI拟声: 5秒内克隆您的声音并生成任意语音内容 Clone a voice in 5 seconds to generate arbitrary speech in real-time

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IQT

Unofficial implementation of CVPR2021 paper "Perceptual Image Quality Assessment with Transformers"

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Deep-Feature-Flow-Segmentation

Deep Feature Flow for Video Semantic Segmentation

Language:PythonMIT3300

Deep-Feature-Flow

Deep Feature Flow for Video Recognition

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MAFFSRN

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IMDN

Lightweight Image Super-Resolution with Information Multi-distillation Network (ACM MM 2019, Winner Award of ICCVW AIM 2019 Constrained SR Track1&Track2)

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pixelmodels

Pixel based Video Quality Models for UHD-1/4K

Language:PythonGPL-3.0300

Deep-Video-Super-Resolution

The state-of-the-art VSR

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HDRTVNet

ICCV2021 - A New Journey from SDRTV to HDRTV.

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distnet

Reference-free distortion map generation and application to no-reference image quality assessment

NOASSERTION500

DBCNN-PyTorch

An experimental Pytorch implementation of Blind Image Quality Assessment Using A Deep Bilinear Convolutional Neural Network

Language:PythonMIT20800

Real-ESRGAN

Real-ESRGAN aims at developing Practical Algorithms for General Image/Video Restoration.

Language:PythonBSD-3-Clause2713400

hyperIQA

Source code for the CVPR'20 paper "Blindly Assess Image Quality in the Wild Guided by A Self-Adaptive Hyper Network"

Language:PythonMIT34900

Pytorch-TestRankIQA

RankIQA model files in Pytorch. Test RankIQA on TID2013 or LIVE dataset in Pytorch.

Language:PythonMIT4600

WaDIQaM

[unofficial] Pytorch implementation of WaDIQaM in TIP2018, Bosse S. et al. (Deep neural networks for no-reference and full-reference image quality assessment)

Language:Python12700