Titlebook: Visual Attributes; Rogerio Schmidt Feris,Christoph Lampert,Devi Parik Book 2017 Springer International Publishing AG 2017 Computer Vision.

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書目名稱Visual Attributes影響因子(影響力)




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Eviction

In the Era of Deep Convolutional Features: Are Attributes Still Useful Privileged Data? computer vision field to solve the object recognition task in images. We want computers to be able to learn more efficiently at the expense of providing extra information during training time. In this chapter, we focus on semantic attributes as a source of additional information about image data. T

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MURAL

哥哥噴涌而出

GEAR

Localizing and Visualizing Relative Attributes In contrast to traditional approaches that use global appearance features or rely on keypoint detectors, our goal is to automatically discover the image regions that are relevant to the attribute, even when the attribute’s appearance changes drastically across its attribute spectrum. To accomplish

Diastole

Deep Learning Face Attributes for Detection and Alignmentage, ethnicity, face shape, and nose size. Predicting face attributes in the wild is challenging due to complex face variations. This chapter aims to provide an in-depth presentation of recent progress and the current state-of-the-art approaches to solving some of the fundamental challenges in face

傲慢物

Visual Attributes for Fashion Analyticsntroduce a system called . for recommending clothing for different occasions, and a system called . for hairstyle and facial makeup recommendation. For fashion retrieval, we describe a cross-domain clothing retrieval system, which receives as input a user photo of a particular clothing item taken in

PALSY

A Taxonomy of Part and Attribute Discovery Techniques. (PnA)-based representations are popular in computer vision as they allow modeling of appearance in a compositional manner, and provide a basis for communication between a human and a machine for various interactive applications. Based on two main properties of these techniques a unified taxonomy o

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