We investigate the problem of estimating the 3D shape of an object, given a set of 2D landmarks in a single image. To alleviate the reconstruction ambiguity, a widely-used approach is to confine the unknown 3D shape within a shape space built upon existing shapes. While this approach has proven to be successful in various applications, a challenging issue remains, i.e., the joint estimation of shape parameters and camera-pose parameters requires to solve a nonconvex optimization problem. The existing methods often adopt an alternating minimization scheme to locally update the parameters, and consequently the solution is sensitive to initialization. In this paper, we propose a convex formulation to address this problem and develop an efficient algorithm to solve the proposed convex program. We demonstrate the exact recovery property of the proposed method, its merits compared to alternative methods, and the applicability in human pose and car shape estimation.

Efficient electrocatalytic overall water splitting is achieved with commercially-available and low-cost nickel foam and stainless steel mesh as cathode and anode electrodes.

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Plasmon-induced magnetic resonance has shown great potentials in optical metamaterials, chemical (bio)-sensing, and surface-enhanced spectroscopies. Here, we have theoretically and experimentally revealed (1) a correspondence of the strongest near-field response to the far-field scattering valley and (2) a significant improvement in Raman signals of probing molecules by the plasmon-induced magnetic resonance. These revelations are accomplished by designing a simple and practical metallic nanoparticle-film plasmonic system that generates magnetic resonances at visible-near-infrared frequencies. Our work may provide new insights for understanding the enhancement mechanism of various plasmon-enhanced spectroscopies and also helps further explore light-matter interactions at the nanoscale.