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  • CVPR 2016 paper reading (2)

    1. Sketch me that shoe, Qian Yu, Feng Liu, Yi-Zhe Song, Tao Xiang, Timothy M. Hospedales, Cheng Change Loy, in CVPR 2016.

    A unique characteristic of sketches in the context of image retrieval is that they offer inherently fine-grained visual description - a sketch speaks for a 'hundred' words.

    fine-grained sketch-based image retrieval (SBIR)面临三个挑战:

    1) visual comparisons not only need to be fine-grained but also executed cross-domain; (sketch和photo是两个不同的domains)

    2) free-hand (finger) sketches are highly abstract, making free-grained matching harder, and most importantly;

    3) annotated cross-domain sketch-photo datasets required for training are scarce.

    this paper introduces two instance-level SBIR datasets consisting of 1432 sketch-photo pairs in two categories (shoes and chairs), collected by asking participants to finger-sketch an object after observing a photo. Besides, a total of 32,000 ground-truth triplet ranking annotations are provided for both model development and performance evaluation.

    this paper uses the annotated triplets as supervision to train triplet CNNs. The goal is to learn a feature mapping f that maps photos and sketches to a common feature embedding space, in which photos similar to pariticular sketches are closer than those dissimilar ones.

    --> Triplet loss:

     实验做得比较周密,考虑了4个步骤的pretrain和fine-tune阶段,并加入了data augmentation(包括stroke removal和stroke deformulation),每一种改进都获得了性能提升。

    千里之行,始于足下~
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  • 原文地址:https://www.cnblogs.com/wm123/p/6481515.html
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