LPIPS metric. pip install lpips
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Updated
May 10, 2024 - Python
LPIPS metric. pip install lpips
A simple and useful implementation of LPIPS.
A metric for Perceptual Image-Error Assessment through Pairwise Preference (PieAPP at CVPR 2018).
Comparing different similarity functions for reconstruction of image on CycleGAN. (https://tandon-a.github.io/CycleGAN_ssim/) Training cycleGAN with different loss functions to improve visual quality of produced images
Experiments with perceptual loss and autoencoders.
A no-reference version of HDR-VDP using deep-learning
[ECCV 2022] We investigated a broad range of neural network elements and developed a robust perceptual similarity metric. Our shift-tolerant perceptual similarity metric (ST-LPIPS) is consistent with human perception and is less susceptible to imperceptible misalignments between two images than existing metrics.
A Study of Deep Perceptual Metrics for Image quality Assessment
Benchmarking library for image manipulation detection.
LPIPS metric on PaddlePaddle. pip install paddle-lpips
[TMLR 2023] as a featured article (spotlight 🌟 or top 0.01% of the accepted papers). In this study, we systematically examine the robustness of both traditional and learned perceptual similarity metrics to imperceptible adversarial perturbations.
Android librarry (kotlin) : Image (JPEG, BMP) comparison (perceptual hash algorithm)
Finetuning and clustering library for image perceptual similarity models.
Clustering slices within NIfTI volume based on Perceptual Similarity or SSIM.
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