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Rethinking FID: Towards a Better Evaluation Metric for Image Generation
The paper criticizes the Fréchet Inception Distance (FID) as an evaluation metric for generated images and proposes an alternative metric called CMMD, which is based on CLIP embeddings and offers a more reliable assessment of image quality.
https://arxiv.org/abs//2401.09603
YouTube: https://www.youtube.com/@ArxivPapers
TikTok: https://www.tiktok.com/@arxiv_papers
Apple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-papers/id1692476016
Spotify: https://podcasters.spotify.com/pod/show/arxiv-papers
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By Igor Melnyk
5
33 ratings
The paper criticizes the Fréchet Inception Distance (FID) as an evaluation metric for generated images and proposes an alternative metric called CMMD, which is based on CLIP embeddings and offers a more reliable assessment of image quality.
https://arxiv.org/abs//2401.09603
YouTube: https://www.youtube.com/@ArxivPapers
TikTok: https://www.tiktok.com/@arxiv_papers
Apple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-papers/id1692476016
Spotify: https://podcasters.spotify.com/pod/show/arxiv-papers
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