Awesome

CVPR2016

Papers about face recognition, face detection, landmark detection, face reconstruction, text detection and so on.

【face】

【Face Recognition】

<ul> <li> Pose-Aware Face Recognition in the Wild, CVPR, 2016. <a href="http://www.cv-foundation.org/openaccess/content_cvpr_2016/papers/Masi_Pose-Aware_Face_Recognition_CVPR_2016_paper.pdf">[Paper]</a></li> </ul></li> <ul> <li> The MegaFace Benchmark: 1 Million Faces for Recognition at Scale, CVPR, 2016. <a href="http://www.cv-foundation.org/openaccess/content_cvpr_2016/papers/Kemelmacher-Shlizerman_The_MegaFace_Benchmark_CVPR_2016_paper.pdf">[Paper]</a></li> </ul></li> <ul> <li> Latent Factor Guided Convolutional Neural Networks for Age-Invariant Face Recognition, CVPR, 2016. <a href="http://www.cv-foundation.org/openaccess/content_cvpr_2016/papers/Wen_Latent_Factor_Guided_CVPR_2016_paper.pdf">[Paper]</a></li> </ul></li> <ul> <li> Discriminative Invariant Kernel Features: A Bells-and-Whistles-Free Approach to Unsupervised Face Recognition and Pose Estimation, CVPR, 2016. <a href="http://www.cv-foundation.org/openaccess/content_cvpr_2016/papers/Pal_Discriminative_Invariant_Kernel_CVPR_2016_paper.pdf">[Paper]</a></li> </ul></li> <ul> <li> CP-mtML: Coupled Projection Multi-Task Metric Learning for Large Scale Face Retrieval, CVPR, 2016. <a href="http://www.cv-foundation.org/openaccess/content_cvpr_2016/papers/Bhattarai_CP-mtML_Coupled_Projection_CVPR_2016_paper.pdf">[Paper]</a></li> </ul></li> <ul> <li> Sparsifying Neural Network Connections for Face Recognition, CVPR, 2016. <a href="http://www.cv-foundation.org/openaccess/content_cvpr_2016/papers/Sun_Sparsifying_Neural_Network_CVPR_2016_paper.pdf">[Paper]</a></li> </ul></li>

【Face Detection】

<ul> <li> Joint Training of Cascaded CNN for Face Detection, CVPR, 2016. <a href="http://www.cv-foundation.org/openaccess/content_cvpr_2016/papers/Qin_Joint_Training_of_CVPR_2016_paper.pdf">[Paper]</a></li> </ul></li> <ul> <li> WIDER FACE: A Face Detection Benchmark, CVPR, 2016. <a href="http://www.cv-foundation.org/openaccess/content_cvpr_2016/papers/Yang_WIDER_FACE_A_CVPR_2016_paper.pdf">[Paper]</a></li> </ul></li>

【Face Alignment】

<ul> <li>Face Alignment Across Large Poses: A 3D Solution, CVPR, 2016. <a href="http://www.cv-foundation.org/openaccess/content_cvpr_2016/papers/Zhu_Face_Alignment_Across_CVPR_2016_paper.pdf">[Paper]</a></li> </ul></li> <ul> <li>Unconstrained Face Alignment via Cascaded Compositional Learning, CVPR, 2016. <a href="http://www.cv-foundation.org/openaccess/content_cvpr_2016/papers/Zhu_Unconstrained_Face_Alignment_CVPR_2016_paper.pdf">[Paper]</a></li> </ul></li> <ul> <li>Occlusion-Free Face Alignment: Deep Regression Networks Coupled With De-Corrupt AutoEncoders, CVPR, 2016. <a href="http://www.cv-foundation.org/openaccess/content_cvpr_2016/papers/Zhang_Occlusion-Free_Face_Alignment_CVPR_2016_paper.pdf">[Paper]</a></li> </ul></li> <ul> <li>Mnemonic Descent Method: A Recurrent Process Applied for End-To-End Face Alignment, CVPR, 2016. <a href="http://www.cv-foundation.org/openaccess/content_cvpr_2016/papers/Trigeorgis_Mnemonic_Descent_Method_CVPR_2016_paper.pdf">[Paper]</a></li> </ul></li> <ul> <li>Large-Pose Face Alignment via CNN-Based Dense 3D Model Fitting, CVPR, 2016. <a href="http://www.cv-foundation.org/openaccess/content_cvpr_2016/papers/Jourabloo_Large-Pose_Face_Alignment_CVPR_2016_paper.pdf">[Paper]</a></li> </ul></li>

【face reconstruction】

<ul> <li>Automated 3D Face Reconstruction From Multiple Images Using Quality Measures, CVPR, 2016. <a href="http://www.cv-foundation.org/openaccess/content_cvpr_2016/papers/Piotraschke_Automated_3D_Face_CVPR_2016_paper.pdf">[Paper]</a></li> </ul></li> <ul> <li>A Robust Multilinear Model Learning Framework for 3D Faces, CVPR, 2016. <a href="http://www.cv-foundation.org/openaccess/content_cvpr_2016/papers/Bolkart_A_Robust_Multilinear_CVPR_2016_paper.pdf">[Paper]</a></li> </ul></li> <ul> <li>Adaptive 3D Face Reconstruction From Unconstrained Photo Collections, CVPR, 2016. <a href="http://www.cv-foundation.org/openaccess/content_cvpr_2016/papers/Roth_Adaptive_3D_Face_CVPR_2016_paper.pdf">[Paper]</a></li> </ul></li> <ul> <li>A 3D Morphable Model Learnt From 10,000 Faces, CVPR, 2016. <a href="http://www.cv-foundation.org/openaccess/content_cvpr_2016/papers/Booth_A_3D_Morphable_CVPR_2016_paper.pdf">[Paper]</a></li> </ul></li>

【other papers about face】

<ul> <li>Recurrent Face Aging, CVPR, 2016. <a href="http://www.cv-foundation.org/openaccess/content_cvpr_2016/papers/Wang_Recurrent_Face_Aging_CVPR_2016_paper.pdf">[Paper]</a></li> </ul></li> <ul> <li>Face2Face: Real-Time Face Capture and Reenactment of RGB Videos, CVPR, 2016. <a href="http://www.cv-foundation.org/openaccess/content_cvpr_2016/papers/Thies_Face2Face_Real-Time_Face_CVPR_2016_paper.pdf">[Paper]</a></li> </ul></li> <ul> <li>Self-Adaptive Matrix Completion for Heart Rate Estimation From Face Videos Under Realistic Conditions, CVPR, 2016. <a href="http://www.cv-foundation.org/openaccess/content_cvpr_2016/papers/Tulyakov_Self-Adaptive_Matrix_Completion_CVPR_2016_paper.pdf">[Paper]</a></li> </ul></li> <ul> <li>CP-mtML: Coupled Projection Multi-Task Metric Learning for Large Scale Face Retrieval, CVPR, 2016. <a href="http://www.cv-foundation.org/openaccess/content_cvpr_2016/papers/Bhattarai_CP-mtML_Coupled_Projection_CVPR_2016_paper.pdf">[Paper]</a></li> </ul></li> <ul> <li>, CVPR, 2016. <a href="">[Paper]</a></li> </ul></li>

【others】

<ul> <li>A Direct Least-Squares Solution to the PnP Problem With Unknown Focal Length, CVPR, 2016. <a href="http://www.cv-foundation.org/openaccess/content_cvpr_2016/papers/Zheng_A_Direct_Least-Squares_CVPR_2016_paper.pdf">[Paper]</a></li> </ul></li> <ul> <li>Ordinal Regression With Multiple Output CNN for Age Estimation, CVPR, 2016. <a href="http://www.cv-foundation.org/openaccess/content_cvpr_2016/papers/Niu_Ordinal_Regression_With_CVPR_2016_paper.pdf">[Paper]</a></li> </ul></li>