lidq92/PyTorch-GAN

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lidq92/PyTorch-GAN

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PyTorch implementations of Generative Adversarial Networks variants

VSFA

[official] Quality Assessment of In-the-Wild Videos (ACM MM 2019)

CNNIQA

[unofficial] CVPR2014-Convolutional neural networks for no-reference image quality assessment

WaDIQaM

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

CNNIQAplusplus

[unofficial] PyTorch Implementation of image quality assessment methods: IQA-CNN++ in ICIP2015 and IQA-CNN in CVPR2014

LinearityIQA

[official] Norm-in-Norm Loss with Faster Convergence and Better Performance for Image Quality Assessment (ACM MM 2020)

MDTVSFA

[official] Unified Quality Assessment of In-the-Wild Videos with Mixed Datasets Training (IJCV 2021)

SFA

[official] No reference image quality assessment based Semantic Feature Aggregation, published in ACM MM 2017, TMM 2019

pytorch-capsule-networks

PyTorch Implementation of Capsule Networks in NIPS2017 and ICLR2018

LSRN-PCGC

[official] DCC 2024: Lightweight super resolution network for point cloud geometry compression

machine-learning-yearning

Chinese Translation of Machine Learning Yearning by Andrew Ng

msmlTMIQA

Quality Assessment for Tone-Mapped HDR Images Using Multi-Scale and Multi-Layer Information (ICMEw 2018)

PCD-PCL

A High-Quality Colored Point Cloud Dataset Provided by Peng Cheng Laboratory (mainly for AVS PCC and PCQA)

IQA4VQA

Best Practices for Initializing Image and Video Quality Assessment Models

selenium_example

Auto search and download similar images (image-crawler)

mmddl

Multimedia Deadlines

lidq92.github.io

Dingquan Li's homepage

sxjzart

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