Extreme 3D Face Reconstruction: Seeing Through Occlusions

Anh Tuan Tran, Tal Hassner, Iacopo Masi, Eran Paz, Yuval Nirkin, Gerard Medioni

نتاج البحث: فصل من :كتاب / تقرير / مؤتمرمنشور من مؤتمرمراجعة النظراء

ملخص

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.

اللغة الأصليةالإنجليزيّة
عنوان منشور المضيفProceedings - 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2018
ناشرIEEE Computer Society
الصفحات3935-3944
عدد الصفحات10
رقم المعيار الدولي للكتب (الإلكتروني)9781538664209
المعرِّفات الرقمية للأشياء
حالة النشرنُشِر - 14 ديسمبر 2018
الحدث31st Meeting of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2018 - Salt Lake City, الولايات المتّحدة
المدة: ١٨ يونيو ٢٠١٨٢٢ يونيو ٢٠١٨

سلسلة المنشورات

الاسمProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
رقم المعيار الدولي للدوريات (المطبوع)1063-6919

!!Conference

!!Conference31st Meeting of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2018
الدولة/الإقليمالولايات المتّحدة
المدينةSalt Lake City
المدة١٨/٠٦/١٨٢٢/٠٦/١٨

ملاحظة ببليوغرافية

Publisher Copyright:
© 2018 IEEE.

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