We present a novel method for modeling 3D face shape, viewpoint, and expression from a single, unconstrained photo. Our method uses three deep convolutional neural networks to estimate each of these components separately. Importantly, unlike others, our method does not use facial landmark detection at test time; instead, it estimates these properties directly from image intensities. In fact, rather than using detectors, we show how accurate landmarks can be obtained as a by-product of our modeling process. We rigorously test our proposed method. To this end, we raise a number of concerns with existing practices used in evaluating face landmark detection methods. In response to these concerns, we propose novel paradigms for testing the effectiveness of rigid and non-rigid face alignment methods without relying on landmark detection benchmarks.

Deep, Landmark-Free FAME: Face Alignment, Modeling, and Expression Estimation / Chang, F; Tran, A; Hassner, T; Masi, I; Nevatia, R; Medioni, G. - In: INTERNATIONAL JOURNAL OF COMPUTER VISION. - ISSN 0920-5691. - (2019). [https://doi.org/10.1007/s11263-019-01151-x]

Deep, Landmark-Free FAME: Face Alignment, Modeling, and Expression Estimation

Masi I;
2019

Abstract

We present a novel method for modeling 3D face shape, viewpoint, and expression from a single, unconstrained photo. Our method uses three deep convolutional neural networks to estimate each of these components separately. Importantly, unlike others, our method does not use facial landmark detection at test time; instead, it estimates these properties directly from image intensities. In fact, rather than using detectors, we show how accurate landmarks can be obtained as a by-product of our modeling process. We rigorously test our proposed method. To this end, we raise a number of concerns with existing practices used in evaluating face landmark detection methods. In response to these concerns, we propose novel paradigms for testing the effectiveness of rigid and non-rigid face alignment methods without relying on landmark detection benchmarks.
facial landmark detector, deep learning, face analysis
01 Pubblicazione su rivista::01a Articolo in rivista
Deep, Landmark-Free FAME: Face Alignment, Modeling, and Expression Estimation / Chang, F; Tran, A; Hassner, T; Masi, I; Nevatia, R; Medioni, G. - In: INTERNATIONAL JOURNAL OF COMPUTER VISION. - ISSN 0920-5691. - (2019). [https://doi.org/10.1007/s11263-019-01151-x]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1458894
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