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We propose a simple, yet powerful regularization technique that can be used to significantly improve both the pairwise and triplet losses in learning local feature descriptors. The idea is that in order to fully utilize the expressive power of the descriptor space, good local feature descriptors should be sufficiently “spread-out” over the space. In this work, we propose a regularization term to maximize...
We focus on the non-Lambertian object-level intrinsic problem of recovering diffuse albedo, shading, and specular highlights from a single image of an object. Based on existing 3D models in the ShapeNet database, a large-scale object intrinsics database is rendered with HDR environment maps. Millions of synthetic images of objects and their corresponding albedo, shading, and specular ground-truth...
In this paper, the characteristics of the kinetic reliability of space four-links mechanism are analyzed and the relationship between the kinetic accuracy and wear clearances in joints is explored, using Advanced First Order and Second Moment (AFOSM) method and Monte-Carlo Simulation (MCS). The Archard wear model is applied to analyze the increasing wear clearances in joints; and the function between...
Attribute-based query offers an intuitive way of image retrieval, in which users can describe the intended search targets with understandable attributes. In this paper, we develop a general and powerful framework to solve this problem by leveraging a large pool of weak attributes comprised of automatic classifier scores or other mid-level representations that can be easily acquired with little or...
The optimization of scaffold mechanical properties for neurite extension is critical for neural tissue engineering. Agarose hydrogels can be used to stimulate and maintain three-dimensional neurite extension from primary sensory ganglia in vitro. The present study explores the structure-function relationship between dorsal root ganglion (DRG) neurite extension and agarose gel mechanical properties...
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