Maximum-Margin Structured Learning with Deep Networks for 3D Human Pose Estimation

Keywords

Pose, Margin (machine learning), Artificial intelligence, Embedding, Computer science

References

• Probabilistic Graphical Models: Principles and Techniques - Adaptive Computation and Machine LearningDaphne Koller, Nir Friedman — 2009
• Multimodal learning with deep Boltzmann machinesNitish Srivastava, Ruslan Salakhutdinov — 2012
• Better Mixing via Deep RepresentationsYoshua Bengio, Grégoire Mesnil, Yann Dauphin — 2012
• Learning representations by back-propagating errorsDavid E. Rumelhart, Geoffrey E. Hinton, Ronald J. Williams — 1986
• Deep Canonical Correlation AnalysisGalen Andrew, Raman Arora, Jeff Bilmes — 2013
• Human Pose Estimation with Iterative Error FeedbackJoão Carreira, Pulkit Agrawal, Katerina Fragkiadaki — 2015
• Deep structured learning for mass segmentation from mammogramsNeeraj Dhungel, Gustavo Carneiro, Andrew P. Bradley — 2014
• A Mathematical Introduction to Robotic ManipulationRichard M. Murray, Zexiang Li, Shankar Sastry — 1994
• Theano: new features and speed improvementsFrédéric Bastien, Pascal Lamblin, Razvan Pascanu — 2012
• Rectified Linear Units Improve Restricted Boltzmann MachinesVinod Nair, Geoffrey E. Hinton — 2010
• Deep Structured Output Learning for Unconstrained Text RecognitionMax Jaderberg, Karen Simonyan, Andrea Vedaldi — 2014
• Learning Human Pose Estimation Features with Convolutional NetworksArjun Jain, Jonathan Tompson, Mykhaylo Andriluka — 2013
• Articulated pose estimation with flexible mixtures-of-partsYi Yang, Deva Ramanan — 2011
• Deep Learning Face Representation from Predicting 10,000 ClassesYi Sun, Xiaogang Wang, Xiaoou Tang — 2014
• Articulated Body Motion Capture by Stochastic SearchJ. Deutscher, Ian Reid — 2005
• Better Appearance Models for Pictorial StructuresMarcin Eichner, Vittorio Ferrari — 2009
• Pictorial Structures for Object RecognitionPedro F. Felzenszwalb, Daniel P. Huttenlocher — 2004
• Cutting-plane training of structural SVMsThorsten Joachims, Thomas Finley, Chun-Nam Yu — 2009
• Heterogeneous Multi-task Learning for Human Pose Estimation with Deep Convolutional Neural NetworkSijin Li, Zhi-Qiang Liu, Antoni B. Chan — 2014
• CNN Features Off-the-Shelf: An Astounding Baseline for RecognitionAli Sharif Razavian, Hossein Azizpour, Josephine Sullivan — 2014

Cited by

• Structural-RNN: Deep Learning on Spatio-Temporal GraphsAshesh Jain, Amir Zamir, Silvio Savarese — 2015
• Synthesizing Training Images for Boosting Human 3D Pose EstimationWenzheng Chen, Huan Wang, Yangyan Li — 2016
• Single-target tracking of arbitrary objects using multi-layered features and contextual informationJingjing Xiao — 2016
• Structured Prediction of 3D Human Pose with Deep Neural NetworksBugra Tekin, Isinsu Katircioglu, Mathieu Salzmann — 2016
• A comparative study of structured prediction methods for sequence labelingA. Cuesta — 2016
• Human activity recognition using deep belief networksHülya Yalçın — 2016
• MoCap-guided Data Augmentation for 3D Pose Estimation in the WildGrégory Rogez, Cordelia Schmid — 2016
• Towards Viewpoint Invariant 3D Human Pose EstimationAlbert Haque, Boya Peng, Zelun Luo — 2016
• 3D Human pose estimation: A review of the literature and analysis of covariatesNikolaos Sarafianos, Bogdan Boteanu, Bogdan Ionescu — 2016
• Monocular 3D object recognitionMenglong Zhu — 2016
• Learning Camera Viewpoint Using CNN to Improve 3D Body Pose EstimationMona Fathollahi Ghezelghieh, Rangachar Kasturi, Sudeep Sarkar — 2016
• Coarse-to-Fine Volumetric Prediction for Single-Image 3D Human PoseGeorgios Pavlakos, Xiaowei Zhou, Konstantinos G. Derpanis — 2016
• Learning to Fuse 2D and 3D Image Cues for Monocular Body Pose EstimationBugra Tekin, Pablo Márquez-Neila, Mathieu Salzmann — 2016
• 3D Human Pose Estimation from a Single Image via Distance Matrix RegressionFrancesc Moreno-Noguer — 2016
• Monocular 3D Human Pose Estimation Using Transfer Learning and Improved CNN SupervisionDushyant Mehta, Helge Rhodin, Dan Casas — 2016
• MonoCap: Monocular Human Motion Capture using a CNN Coupled with a Geometric PriorXiaowei Zhou, Menglong Zhu, Georgios Pavlakos — 2017
• Lifting from the Deep: Convolutional 3D Pose Estimation from a Single ImageDenis Tomè, Chris Russell, Lourdes Agapito — 2017
• Deep Multitask Architecture for Integrated 2D and 3D Human SensingAlin-Ionut Popa, Mihai Zanfir, Cristian Sminchisescu — 2017
• Automatic Quantification of Tumour Hypoxia From Multi-Modal Microscopy Images Using Weakly-Supervised Learning MethodsGustavo Carneiro, Tingying Peng, Christine Bayer — 2017
• Learning from Natural Human Interactions for Assistive RobotsAshesh Jain — 2016

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