3 research outputs found
Advanced concepts for intelligent vision systems, 19th international conference, ACIVS 2018, proceedings
International audienceThis book constitutes the refereed proceedings of the 19th International Conference on Advanced Concepts for Intelligent Vision Systems, ACIVS 2018, held in Poitiers, France, in September 2018. The 52 full papers presented in this volume were carefully reviewed and selected from 91 submissions. They were organized in topical sections named: video analysis; segmentation and classification; remote sending; biometrics; deep learning; coding and compression; and image restauration and reconstruction
AgingMapGAN (AMGAN): High-Resolution Controllable Face Aging with Spatially-Aware Conditional GANs
Existing approaches and datasets for face aging produce results skewed
towards the mean, with individual variations and expression wrinkles often
invisible or overlooked in favor of global patterns such as the fattening of
the face. Moreover, they offer little to no control over the way the faces are
aged and can difficultly be scaled to large images, thus preventing their usage
in many real-world applications. To address these limitations, we present an
approach to change the appearance of a high-resolution image using
ethnicity-specific aging information and weak spatial supervision to guide the
aging process. We demonstrate the advantage of our proposed method in terms of
quality, control, and how it can be used on high-definition images while
limiting the computational overhead.Comment: Project page: https://despoisj.github.io/AgingMapGAN
Recursive Chaining of Reversible Image-to-Image Translators for Face Aging
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.Peer reviewe