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Human pose estimation requires a versatile yet well-constrained spatial model for grouping locally ambiguous parts together to produce a globally consistent hypothesis. Previous works either use local deformable models deviating from a certain template, or use a global mixture representation in the pose space. In this paper, we propose a new hierarchical(More)
Digital photo management is becoming indispensable for the explosively growing family photo albums due to the rapid popularization of digital cameras and mobile phone cameras. In an effective photo management system photo annotation is the most challenging task. In this paper, we develop several innovative interaction techniques for semi-automatic photo(More)
A video sequence of an underwater scene taken from above the water surface suffers from severe distortions due to water fluctuations. In this paper, we simultaneously estimate the shape of the water surface and recover the pla-nar underwater scene without using any calibration patterns , image priors, multiple viewpoints or active illumination. The key idea(More)
Competing with top human players in the ancient game of Go has been a long-term goal of artificial intelligence. Go's high branching factor makes traditional search techniques ineffective, even on leading-edge hardware, and Go's evaluation function could change drastically with one stone change. Recent works [Maddi-son et al. (2015); Clark & Storkey (2015)](More)
Face annotation technology is important for a photo management system. In this paper, we propose a novel interactive face annotation framework combining unsuper-vised and interactive learning. There are two main contributions in our framework. In the unsupervised stage, a partial clustering algorithm is proposed to find the most evident clusters instead of(More)
Image alignment in the presence of non-rigid distortions is a challenging task. Typically, this involves estimating the parameters of a dense deformation field that warps a distorted image back to its undistorted template. Generative approaches based on parameter optimization such as Lucas-Kanade can get trapped within local minima. On the other hand,(More)
Most active scene recovery techniques assume that a scene point is illuminated only directly by the illumination source. Consequently, global illumination effects due to inter-reflections, sub-surface scattering and volumetric scattering introduce strong biases in the recovered scene shape. Our goal is to recover scene properties in the presence of global(More)
A fundamental challenge in face recognition lies in determining what facial features are important for the identification of faces. In this paper, a novel face recognition framework is proposed to address this problem. In our framework, 3D face models are used to synthesize a huge database of realistic face images which covers wide appearance variations of(More)