2014
DOI: 10.48550/arxiv.1411.7964
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Effective Face Frontalization in Unconstrained Images

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Cited by 3 publications
(4 citation statements)
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“…2. Note that the type I artefacts are generated by not only our method but also 3D synthesis methods such as [30], [58], [12]. As shown in the top-right side of Fig.…”
Section: B Compositing Artefactsmentioning
confidence: 95%
See 1 more Smart Citation
“…2. Note that the type I artefacts are generated by not only our method but also 3D synthesis methods such as [30], [58], [12]. As shown in the top-right side of Fig.…”
Section: B Compositing Artefactsmentioning
confidence: 95%
“…Our method 3D synthesis illumination pose Fig. 2: Top row: Type I hard boundary artefacts generated by our method (left) and 3D synthesis methods [30], [58], [12] (right). Bottom row: Type II artefacts due to inconsistencies in illumination (left) and pose (right) generated by our method.…”
Section: Face Recognition Pipelinementioning
confidence: 99%
“…With these exertions, the traditional face recognition problem is re-defined, shifting from the strictly regulated setting to the unconstrained condition with severe intra-variabilities, e.g., the LFW and the YouTube Faces (YTF) images. This evolvement stimulates enormous research on pose-invariant face recognition, e.g., [35][36][37].…”
Section: A Related Workmentioning
confidence: 99%
“…This ranges from rough centering in Schroff, Florian and Kalenichenko 2015 to the use of a 3D face mask estimate and re-projection of the 2D image as in Hassner, Tal, et al 2014. 5,31 5. DATASETS…”
Section: The State-of-the-art In Facial Recognitionmentioning
confidence: 99%