ECCV Paper List

Excerpt ECCV2016 part of the article, mainly Human pose esimation, Human activiity/actions, face alignment, face Detection & recognition & .. , Hand tracking, eye, and Others.

The following is the article and title (may have errors and omissions)

Human Pose Estimation:

[1] Towards Viewpoint invariant 3DHuman Pose estimation

Albert Haque, Boya Peng, Zelun Luo, Alexandre Alahi, Serena Yeung, andLi Fei-fei

[2] Fast 6D Pose estimation from amonocular Image Usinghierarchical Pose Trees

Yoshinori Konishi, Yuki Hanzawa, Masato kawade, andManabu Hashimoto

[3] Keep It smpl:automaticestimation of 3D Human Pose and Shape froma singleimage

Federica Bogo, Angjoo Kanazawa, Christoph Lassner, Peter gehler,Javier Romero, and Michael J. Black

[4] Zoom Better to see Clearer:human and Object parsing withhierarchicalauto-zoom Net

fangting Xia, Pengwang, Liang-chieh Chen, and Alan L. Yuille

[5] A sequential approach to 3D Human Pose estimation:separation ofLocalization and identification of Body joints

Ho Yub Jung, Yuminsuh, Gyeongsik Moon, and Kyoung Mu Lee

[6] deepercut:a deeper, Stronger,and Faster multi-person Pose estimationModel

Eldar Insafutdinov, Leonid Pishchulin, Bjoern Andres,Mykhaylo Andriluka, and Bernt Schiele

[7] Human Attribute Recognition bydeep hierarchical contexts

yining Li, Chen Huang, Chen Change Loy, and Xiaoou Tang

[8] Human Pose estimation usingdeep Consensus voting .

Ita Lifshitz, Ethan Fetaya, and Shimon Ullman

[9] Human Pose Estimation viaconvolutional part heatmap Regression

Adrian Bulat and Georgios Tzimiropoulos

[10] stacked Hourglass Networks forhuman Pose estimation

Alejandro Newell, Kaiyu Yang, and Jia Deng

[11] Bayesian Image Based 3D poseestimation

Marta Sanzari, Valsamis Ntouskos, and Fiora Pirri

[12] Shape from Selfies:human bodyshape estimation Using CCARegression forests

Endri Dibra, Cengiz Ztireli, Remo Ziegler, and Markus Gross

[13] estimation of Human Body Shapein Motion with Wide clothing

Jinlong Yang, Jean-sébastien Franco, Franck Hétroy-wheeler, andStefanie wuhrer

[14] Chained predictions usingconvolutional neural Networks

Georgia Gkioxari, Alexander Toshev, and Navdeep jaitly

Human activity:

[1] real-time rgb-d activityprediction by Soft Regression

Jian-fang Hu, Wei-shizheng, Lianyang Ma, Gang Wang, andJianhuang Lai

[2] Learning Models for Actionsand Person-object Interactions with Transfer toquestionanswering

Arun Mallya and Svetlana LaZebnik

[3] RNN Fisher Vectors for actionrecognition and Image Annotation.

Guy Lev, Gil Sadeh, Benjamin Klein, and Lior Wolf

[4] Online Human Action detectionusing Joint classification-regressionrecurrent neuralnetworks

Yanghao Li, cuiling Lan, Junliang Xing, Wenjun Zeng, Chunfeng Yuan, andjiaying Liu

[5] Daps:deep Action Proposalsfor Action Understanding

Victor Escorcia, Fabian Caba Heilbron, Juan Carlos niebles, andBernard Ghanem

[6] spatio-temporal LSTM withtrust Gates for 3D HumanAction recognition

June Liu, Amir Shahroudy, Dong Xu, and Gang Wang

[7] multi-region two-stream r-cnnfor Action Detection

Xiaojiang Peng and Cordelia Schmid

Face alignment:

[1] A recurrent encoder-decodernetwork for sequential face Alignment

Xi Peng, Rogerio S. Feris, Xiaoyu Wang, and Dimitris N. Metaxas

[2] Robust facial landmarkdetection via recurrent attentive-refinementNetworks

Shengtao Xiao, Jiashi Feng, Junliang Xing, Hanjiang Lai,Shuicheng Yan, and Ashraf Kassim

[3] Deep deformation Network forobject Landmark Localization

Xiang Yu, Feng Zhou, and Manmohanchandraker

[4] Joint face Alignment and 3DFace reconstruction

Feng Liu, Dan Zeng, Qijun Zhao, and Xiaoming Liu

[5] robust face Alignment Using amixture of invariant experts

Oncel Tuzel, Tim K. Marks, and Salil Tambe

Face Detection & recognition& ...:

[1] moon:a Mixed Objective optimization Networkfor the recognition offacial Attributes

Ethan M. Rudd, Manuel Günther, and Terrance E. Boult

[2] supervised Transformer networkfor efficient face Detection

Dong Chen, Gang Hua,fang Wen, and Jian Sun

[3] ultra-resolving face Images bydiscriminative generative Networks

Xin Yu and Fatih Porikli

[4] Do We really need to collectmillions of Faces for effective facerecognition?

Iacopo Masi, Anh tu?n tr?n, Tal hassner,jatuporn Toy leksut, andGérard Medioni

[5] Deep cascaded bi-network forface hallucination

Shizhan Zhu, Sifeiliu, Chen change Loy, and Xiaoou Tang

[6] Real-time facial Segmentationand performance Capture from RGB Input

Shunsuke Saito, Tianye Li, and Hao Li

[7] cascaded Continuous regressionfor real-time Incremental face Tracking

Enrique Sánchez-lozano, Brais Martinez, Georgios Tzimiropoulos, andMichel Valstar

[8] ms-celeb-1m:a Dataset Andbenchmark for large-scale facerecognition

Yandong Guo, Leizhang, Yuxiao Hu, Xiaodong He, and Jianfeng Gao

[9] Joint face representationadaptation and clustering in Videos.

Zhanpeng Zhang, Ping Luo, Chen change Loy, and Xiaoou Tang

[10] Grid loss:detecting occludedfaces

Michael Opitz, Georg Waltner, Georg poier, Horst Possegger, andHorst Bischof

[11] Face Detection with end-to-endintegration of a convnet and a 3D Model

Yunzhu Li, Benyuansun, Tianfu Wu, and Yizhou Wang

[12] Face recognition from Multiplestylistic Sketches:scenarios, Datasets, andEvaluation

chunlei Peng,nannan Wang, Xinbo Gao, and Jie Li

[13] Fast face Sketch Synthesis viakd-tree Search

Yuqian Zhang,nannan Wang, Shengchuan Zhang, Jie Li, andXinbo Gao

Eye:

[1] A 3D morphable eye regionmodel for gaze estimation

Erroll Wood, Tadas Baltru?aitis, Louis-philippe morency,Peter Robinson, and Andreas bulling

Hand:

[1] real-time Joint Tracking of Ahand manipulating an Object fromrgb-d Input

Srinath Sridhar, Franziska Mueller, Michael zollh?fer, Dan Casas,Antti Oulasvirta, and Christian Theobalt

[2] Spatial Attention Deep netwith Partial PSO for hierarchical HybridHand poseestimation

Qi Ye, Shanxin Yuan, and Tae-kyun Kim

[3] Hand Pose estimation fromlocal Surface Normals

Chengde Wan, Angelayao, and Luc Van Gool

Others:

[1] Doc:deep occlusion estimationfrom a single Image.

Peng Wang and Alanyuille

[2] convolutional orientedboundaries

Kevis-kokitsi Maninis, Jordi pont-tuset, Pablo Arbeláez, andLuc Van Gool

[3] Superpixel convolutionalnetworks Using bilateral inceptions

raghudeep Gadde, Varunjampani, Martin Kiefel, Daniel Kappler, andPeter v.gehler

[4] sdf-2-sdf:highly Accurate 3DObject reconstruction

Miroslava Slavcheva,wadim Kehl, Nassir Navab, and Slobodan Ilic

[5] Learning to Hash with Binarydeep neural Network

Thanh-toan Do,anh-dzung Doan, and Ngai-man Cheung

[6] going further with point Pairfeatures

Stefan Hinterstoisser, Vincent Lepetit, Naresh Rajkumar, andKurt konolige

[7] Automatic Attribute discoverywith Neural Activations

Sirionvittayakorn, Takayuki Umeda, Kazuhiko Murasaki, Kyoko Sudo,Takayuki Okatani, and KotaYamaguchi

ECCV Paper List