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X-WR-CALNAME:GREYC UMR CNRS 6072 - Groupe de Recherche en Informatique, Image, et Instrumentation de Caen
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X-WR-CALDESC:évènements pour GREYC UMR CNRS 6072 - Groupe de Recherche en Informatique, Image, et Instrumentation de Caen
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DTSTART;TZID=Europe/Paris:20240530T140000
DTEND;TZID=Europe/Paris:20240530T153000
DTSTAMP:20260422T043922
CREATED:20240418T152924Z
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UID:11481-1717077600-1717083000@www.greyc.fr
SUMMARY:Séminaire IMAGE : "Navigating the Evaluation Landscape: From Scalar Metrics to Parametrized Curves in Generative Model Assessment" (Benjamin Sykes)
DESCRIPTION:Nous aurons le plaisir d’écouter Benjamin Sykes\, doctorant de l’équipe IMAGE du GREYC.\nIl donnera un séminaire IMAGE\, le jeudi 30 mai 2024\, à 14h00\, en salle de séminaire F-200.\nTitre: « Navigating the Evaluation Landscape: From Scalar Metrics to Parametrized Curves in Generative Model Assessment »\nRésumé: \n\n\n\nWhile it seems fairly easy to evaluate the « quality » of a generative model’s output\, finding a metric that intrinsically quantifies the performance of the model remains a difficult task\, let alone defining what a « performant generative model » in fact means.\n\nWhereas most generative models outputs are still evaluated with some scalar values such as Fréchet Inception Distance (FID) or Inception Score (IS)\, in the last years (Sajjadi et al.\, 2018) proposed a definition of precision and recall for distributions (PRD) with an interpretation as a precision-recall curve\, therefore transposing a concept already used and accepted in binary classification. Since then\, various different approaches to precision and recall have seen the light (Kynkaanniemi et al.\, 2019)\, (Park et al.\, 2023)\, (Naeem et al.\, 2020). While those implementations of precision and recall tend to jointly simplify the computations\, give an intuition of the algorithms and aim at reducing the effects of outliers\, they do have noticeable short-comings such as the fact they are based solely on some intuition and they overlook the initial and mathematically grounded definition of precision and recall as a trade-off curve.\n\nAfter presenting the generative model evaluation landscape by presenting the existing evaluation metrics (FID\, IS\, PRD\, Improved Precision Recall\, Density Coverage). We will then motivate the use of precision and recall as parametrised curves as opposed to two scalar metrics.  We will finally present our unifying setting in which we extend common scalar PR metrics to PRD curves using the binary classification approach from (Simon et al.\, 2019).\n\n\n/ \nRéférences :\n\n\n\n\n\n– Kynkäänniemi\, T.\, Karras\, T.\, Laine\, S.\, Lehtinen\, J.\, & Aila\, T. (2019). Improved Precision and Recall Metric for Assessing Generative Models. Advances in Neural Information Processing Systems\, 32. https://proceedings.neurips.cc/paper_files/paper/2019/hash/0234c510bc6d908b28c70ff313743079-Abstract.html\n\n\n– Naeem\, M. F.\, Oh\, S. J.\, Uh\, Y.\, Choi\, Y.\, & Yoo\, J. (2020). Reliable Fidelity and Diversity Metrics for Generative Models. Proceedings of the 37th International Conference on Machine Learning\, 7176–7185. https://proceedings.mlr.press/v119/naeem20a.html\n\n\n– Park\, D.\, & Kim\, S. (2023). Probabilistic Precision and Recall Towards Reliable Evaluation of Generative Models. 20099–20109.\nhttps://openaccess.thecvf.com/content/ICCV2023/html/Park_Probabilistic_Precision_and_Recall_Towards_Reliable_Evaluation_of_Generative_Models_ICCV_2023_paper.html\n\n\n– Sajjadi\, M. S. M.\, Bachem\, O.\, Lucic\, M.\, Bousquet\, O.\, & Gelly\, S. (2018). Assessing Generative Models via Precision and Recall. Advances in Neural Information Processing Systems\, 31. https://proceedings.neurips.cc/paper_files/paper/2018/hash/f7696a9b362ac5a51c3dc8f098b73923-Abstract.html\n\n\n– Simon\, L.\, Webster\, R.\, & Rabin\, J. (2019). Revisiting precision recall definition for generative modeling. Proceedings of the 36th International Conference on Machine Learning\, 5799–5808. https://proceedings.mlr.press/v97/simon19a.html\n\n\n\n\n/ \nOn vous y attend nombreux !
URL:https://www.greyc.fr/event/seminaire-image-navigating-the-evaluation-landscape-from-scalar-metrics-to-parametrized-curves-in-generative-model-assessment-benjamin-sykes/
LOCATION:ENSICAEN – Batiment F – Salle F-200\, 6 Bd Maréchal Juin\, Caen\, 14050\, France
CATEGORIES:Image,Seminaire Image
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