Papers Reading List in CVPR 2016

Hand Pose Estimation

Robust 3D Hand Pose Estimation in Single Depth Images: From Single-View CNN to Multi-View CNNs.

[pdf] [Homepage]
Liuhao Ge, Hui Liang, Junsong Yuan, Daniel Thalmann
Nanyang Technological University, Singapore

DeepHand: Robust Hand Pose Estimation by Completing a Matrix Imputed With Deep Features.

[pdf][Homepage]
Ayan Sinha, Chiho Choi, Karthik Ramani
Purdue University

Efficiently Creating 3D Training Data for Fine Hand Pose Estimation.

[pdf] [Homepage]
Markus Oberweger, Gernot Riegler, Paul Wohlhart, Vincent Lepetit
Graz University of Technology, Austria

Fits Like a Glove: Rapid and Reliable Hand Shape Personalization.

[pdf] [Homepage]
David Joseph Tan, Thomas Cashman, Jonathan Taylor, Andrew Fitzgibbon, Daniel Tarlow, Sameh Khamis, Shahram Izadi, Jamie Shotton
Microsoft Research
Technische Universitat Munchen

Hand Gesture Recognition

Deep Hand: How to Train a CNN on 1 Million Hand Images When Your Data Is Continuous and Weakly Labelled.

[pdf] [Homepage]
Oscar Koller, Hermann Ney, Richard Bowden
RWTH Aachen University, Germany
University of Surrey, UK

Online Detection and Classification of Dynamic Hand Gestures With Recurrent 3D Convolutional Neural Network.

[pdf][Homepage]
Pavlo Molchanov, Xiaodong Yang, Shalini Gupta, Kihwan Kim, Stephen Tyree, Jan Kautz
NVIDIA

Hand Workshop

Skeleton-based Dynamic hand gesture recognition

[pdf][Homepage]
Quentin De Smedt, Hazem Wannous, Jean-Philippe Vandeborre
Telecom Lille, Univ. Lille

Learning Marginalization through Regression for Hand Orientation Inference

[pdf][Homepage]
Muhammad Asad and Greg Slabaugh
City University London

Hidden Hands: Tracking Hands with an Occlusion Aware Tracker

[pdf][[Homepage]]
Akshay Rangesh, Eshed Ohn-Bar, and Mohan M. Trivedi
University of California, San Diego

Effectiveness of Grasp Attributes and Motion-Constraints for Fine-Grained Recognition of Object Manipulation Actions

[pdf][[Homepage]]
Kartik Gupta, Darius Burschka, Arnav Bhavsar
IIT Mandi, India
TU Munich, Germany