CA-GAN: Weakly Supervised Color Aware GAN for Controllable Makeup Transfer

While existing makeup style transfer models perform an image synthesis whose results cannot be explicitly controlled, the ability to modify makeup color continuously is a desirable property for virtual try-on applications. We propose a new formulation for the makeup style transfer task, with the objective to learn a color controllable makeup style synthesis. We introduce CA-GAN, a generative model that learns to modify the color of specific objects (e.g. lips or eyes) in the image to an arbitrary target color while preserving background. Since color labels are rare and costly to acquire, our method leverages weakly supervised learning for conditional GANs. This enables to learn a controllable synthesis of complex objects, and only requires a weak proxy of the image attribute that we desire to modify. Finally, we present for the first time a quantitative analysis of makeup style transfer and color control performance

Social Interactions in the Labor Market

We examine theoretically and empirically social interactions in labor markets and how policy prescriptions can change dramatically when there are social interactions present. Spillover effects increase labor supply and conformity effects make labor supply perfectly inelastic at a reference group average. The demand for a good may also be influenced by either a spillover effect or a conformity effect. Positive spillover increases the demand for the good with interactions, and a conformity effect makes the demand curve pivot to become less price sensitive. Similar social interactions effects appear in the associated derived demands for labor. Individual and community factors may influence the average length of poverty spells. We measure local economic conditions by the county unemployment rate and neighborhood spillover effects by the racial makeup and poverty rate of the county. We find that moving an individual from one standard deviation above the mean poverty rate to one standard deviation below the mean poverty rate (from the inner city to the suburbs) lowers the average poverty spell by 20–25 percent. We further consider overall labor market outcomes by examining theoretically the socially optimal wealth distribution. Interdependence in utility can mitigate the need to transfer wealth to low-wage individuals and may require them to be poorer by all objective measures. Finally, we quantify how labor market policy changes when there are household social interactions. Labor supply estimates indicate positive economically important spillovers for adult U.S. men. Ignoring or incorrectly considering social interactions can mis-estimate the labor supply response of tax reform in the United States by as much as 60 percent.social interactions, spillover, conformity, inequality, poverty, labor supply, reference group, social multiplier, income tax, PSID

3D Human Face Reconstruction and 2D Appearance Synthesis

3D human face reconstruction has been an extensive research for decades due to its wide applications, such as animation, recognition and 3D-driven appearance synthesis. Although commodity depth sensors are widely available in recent years, image based face reconstruction are significantly valuable as images are much easier to access and store. In this dissertation, we first propose three image-based face reconstruction approaches according to different assumption of inputs. In the first approach, face geometry is extracted from multiple key frames of a video sequence with different head poses. The camera should be calibrated under this assumption. As the first approach is limited to videos, we propose the second approach then focus on single image. This approach also improves the geometry by adding fine grains using shading cue. We proposed a novel albedo estimation and linear optimization algorithm in this approach. In the third approach, we further loose the constraint of the input image to arbitrary in the wild images. Our proposed approach can robustly reconstruct high quality model even with extreme expressions and large poses. We then explore the applicability of our face reconstructions on four interesting applications: video face beautification, generating personalized facial blendshape from image sequences, face video stylizing and video face replacement. We demonstrate great potentials of our reconstruction approaches on these real-world applications. In particular, with the recent surge of interests in VR/AR, it is increasingly common to see people wearing head-mounted displays. However, the large occlusion on face is a big obstacle for people to communicate in a face-to-face manner. Our another application is that we explore hardware/software solutions for synthesizing the face image with presence of HMDs. We design two setups (experimental and mobile) which integrate two near IR cameras and one color camera to solve this problem. With our algorithm and prototype, we can achieve photo-realistic results. We further propose a deep neutral network to solve the HMD removal problem considering it as a face inpainting problem. This approach doesn\u27t need special hardware and run in real-time with satisfying results