V2V-PoseNet: Voxel-to-Voxel Prediction Network for Accurate 3D Hand and Human Pose Estimation from a Single Depth Map

Most of the existing deep learning-based methods for 3D hand and human pose estimation from a single depth map are based on a common framework that takes a 2D depth map and directly regresses the 3D coordinates of keypoints, such as hand or human body joints, via 2D convolutional neural networks (CNNs). The first weakness of this approach is the presence of perspective distortion in the 2D depth map. While the depth map is intrinsically 3D data, many previous methods treat depth maps as 2D images that can distort the shape of the actual object through projection from 3D to 2D space. This compels the network to perform perspective distortion-invariant estimation. The second weakness of the conventional approach is that directly regressing 3D coordinates from a 2D image is a highly non-linear mapping, which causes difficulty in the learning procedure. To overcome these weaknesses, we firstly cast the 3D hand and human pose estimation problem from a single depth map into a voxel-to-voxel prediction that uses a 3D voxelized grid and estimates the per-voxel likelihood for each keypoint. We design our model as a 3D CNN that provides accurate estimates while running in real-time. Our system outperforms previous methods in almost all publicly available 3D hand and human pose estimation datasets and placed first in the HANDS 2017 frame-based 3D hand pose estimation challenge. The code is available in https://github.com/mks0601/V2V-PoseNet_RELEASE.Comment: HANDS 2017 Challenge Frame-based 3D Hand Pose Estimation Winner (ICCV 2017), Published at CVPR 201

Social Norms, Information and Trust among Strangers: Theory and Evidence

Can a social norm of trust and reciprocity emerge among strangers? We investigate this question by examining behavior in an experiment where subjects repeatedly play a two-player binary ―trust‖ game. Players are randomly and anonymously paired with one another in each period. The main questions addressed are whether a social norm of trust and reciprocity emerges under the most extreme information restriction (anonymous community-wide enforcement) or whether trust and reciprocity require additional, individual-specific information about a player’s past history of play and whether that information must be provided freely or at some cost. In the absence of such reputational information, we find that a social norm of trust and reciprocity is difficult to sustain. The provision of reputational information on past individual decisions significantly increases trust and reciprocity, with longer histories yielding the best outcomes. Importantly, we find that making reputational information available at a small cost may also lead to a significant improvement in trust and reciprocity, despite the fact that most subjects do not choose to purchase this information.Social Norms, Trust Game, Random Matching, Trust and Reciprocity, Information, Reputational Mechanisms, Experimental Economics.

Economic Activities and Networks of Relatioships

The fundamental question I address in the dissertation is how the behavior of economic agents interacts with networks of relationships which underlie a wide set of economic situations. In Ch. 2, entitled "Decentralized Information Sharing in Oligopoly," I analyze the incentives of firms for information sharing in a decentralized environment when firms face a stochastic demand. In order to do that, I develop a two stage model of strategic network formation, where a cooperative network formation stage is played in the first stage and a noncooperative Bayesian Cournot game is played in the second stage. I derive pure strategy mixed cooperative and noncooperative equilibria that are subgame perfect and stable, and characterize the resulting network structures. Ch. 3, entitled "A War of Attrition in Network Formation," investigates the strategic behavior of agents when they face a decision on the formation of relationships. I apply a war of attrition to the dynamic network formation process when links among agents have characteristics of public goods. Agents are randomly but exogenously matched in each stage. Based on Bala and Goyal's (2000) two-way flow model, I characterize the subgame-perfect equilibrium outcomes and discuss their efficiency. Finally, Ch. 4, entitled "Social Norms and Trust among Strangers," (with Huan Xie) studies the development of trust and reciprocity among strangers in the indefinitely repeated trust game with random matching. If reputation is attached to the community as a whole and if a single defection leads to the destruction of the cooperative social norm through contagious punishments, the cooperative social norm can be sustained by the self-interested community members in the equilibrium. We provide sufficient conditions that support the social norm of trust and reciprocity as a sequential equilibrium