[CVPRW oral 2022] MANIQA: Multi-dimension Attention Network for No-Reference Image Quality Assessment
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Updated
Jun 10, 2023 - Python
[CVPRW oral 2022] MANIQA: Multi-dimension Attention Network for No-Reference Image Quality Assessment
[ Official ] - PIPAL Dataset and Training Codebase. ECCV-2020, NTIRE-21/22.
A C++ porting of Frank E. Curtis's penalty-interior-point algorithm for nonlinear constrained optimization
Swin Transformer backbone experiment for full-reference image quality assessment (NTIRE 2022)
Takes pipal.rb output and formats into a docx for use in MS word report templates
Multi-scale features + parallel transformers for full-reference image quality assessment (arXiv:2204.09779, NTIRE 2022 @ CVPRW)
IQT baseline + natural scene statistics (MSCN/BRISQUE) features for full-reference IQA on PIPAL
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