A metric for Perceptual Image-Error Assessment through Pairwise Preference (PieAPP at CVPR 2018).
[ECCV 2024] Enhancing Perceptual Quality in Video Super-Resolution through Temporally-Consistent Detail Synthesis using Diffusion Models
[ Official ] - PIPAL Dataset and Training Codebase. ECCV-2020, NTIRE-21/22.
Learning-based Just-noticeable-quantization-distortion Model for perceptual video coding
Code for "Adversarial and Perceptual Refinement Compressed Sensing MRI Reconstruction"
Official code (Pytorch) for paper Perception-Enhanced Single Image Super-Resolution via Relativistic Generative Networks
Supplementary material for the paper "BL-JUNIPER: A CNN Assisted Framework for Perceptual Video Coding Leveraging Block Level JND", IEEE TMM 2022
Full-Reference Image Quality Assessment models based on ensemble of gradient boosting
Supplementary material for the paper "MTJND: MULTI-TASK DEEP LEARNING FRAMEWORK FOR IMPROVED JND PREDICTION", IEEE ICIP 2023
Full-reference objective quality index for reconstructed background images.
Supplementary material for the paper "Lightweight Multitask Learning for Robust JND Prediction using Latent Space and Reconstructed Frames", IEEE TCSVT, 2024.
Super Resolution
Supplementary material for the paper "PERCEPTUAL LEARNED IMAGE COMPRESSION VIA END-TO-END JND-BASED OPTIMIZATION", IEEE ICIP 2024
Add a description, image, and links to the perceptual-quality topic page so that developers can more easily learn about it.
To associate your repository with the perceptual-quality topic, visit your repo's landing page and select "manage topics."