Recursive Chaining of Reversible Image-to-Image Translators for Face Aging

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussavertaisarvioitu

Tutkijat

Organisaatiot

  • GenMind Ltd.

Kuvaus

This paper addresses the modeling and simulation of progressive changes over time, such as human face aging. By treating the age phases as a sequence of image domains, we construct a chain of transformers that map images from one age domain to the next. Leveraging recent adversarial image translation methods, our approach requires no training samples of the same individual at different ages. Here, the model must be flexible enough to translate a child face to a young adult, and all the way through the adulthood to old age. We find that some transformers in the chain can be recursively applied on their own output to cover multiple phases, compressing the chain. The structure of the chain also unearths information about the underlying physical process. We demonstrate the performance of our method with precise and intuitive metrics, and visually match with the face aging state-of-the-art.

Yksityiskohdat

AlkuperäiskieliEnglanti
OtsikkoAdvanced Concepts for Intelligent Vision Systems - 19th International Conference, ACIVS 2018, Proceedings
TilaJulkaistu - 1 tammikuuta 2018
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisuussa
TapahtumaInternational Conference on Advanced Concepts for Intelligent Vision Systems - Poitiers, Ranska
Kesto: 24 syyskuuta 201827 syyskuuta 2018
Konferenssinumero: 19

Julkaisusarja

NimiLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
KustantajaSpringer
Vuosikerta11182 LNCS
ISSN (painettu)0302-9743
ISSN (elektroninen)1611-3349

Conference

ConferenceInternational Conference on Advanced Concepts for Intelligent Vision Systems
LyhennettäACIVS
MaaRanska
KaupunkiPoitiers
Ajanjakso24/09/201827/09/2018

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