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A survey of face recognition techniques under occlusion
The limited capacity to recognize faces under occlusions is a long-standing
problem that presents a unique challenge for face recognition systems and even
for humans. The problem regarding occlusion is less covered by research when
compared to other challenges such as pose variation, different expressions,
etc. Nevertheless, occluded face recognition is imperative to exploit the full
potential of face recognition for real-world applications. In this paper, we
restrict the scope to occluded face recognition. First, we explore what the
occlusion problem is and what inherent difficulties can arise. As a part of
this review, we introduce face detection under occlusion, a preliminary step in
face recognition. Second, we present how existing face recognition methods cope
with the occlusion problem and classify them into three categories, which are
1) occlusion robust feature extraction approaches, 2) occlusion aware face
recognition approaches, and 3) occlusion recovery based face recognition
approaches. Furthermore, we analyze the motivations, innovations, pros and
cons, and the performance of representative approaches for comparison. Finally,
future challenges and method trends of occluded face recognition are thoroughly
discussed
Extreme 3D Face Reconstruction: Seeing Through Occlusions
Existing single view, 3D face reconstruction methods can produce beautifully
detailed 3D results, but typically only for near frontal, unobstructed
viewpoints. We describe a system designed to provide detailed 3D
reconstructions of faces viewed under extreme conditions, out of plane
rotations, and occlusions. Motivated by the concept of bump mapping, we propose
a layered approach which decouples estimation of a global shape from its
mid-level details (e.g., wrinkles). We estimate a coarse 3D face shape which
acts as a foundation and then separately layer this foundation with details
represented by a bump map. We show how a deep convolutional encoder-decoder can
be used to estimate such bump maps. We further show how this approach naturally
extends to generate plausible details for occluded facial regions. We test our
approach and its components extensively, quantitatively demonstrating the
invariance of our estimated facial details. We further provide numerous
qualitative examples showing that our method produces detailed 3D face shapes
in viewing conditions where existing state of the art often break down.Comment: Accepted to CVPR'18. Previously titled: "Extreme 3D Face
Reconstruction: Looking Past Occlusions
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