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arXiv · 1811.02949

Instance Retrieval at Fine-grained Level Using Multi-Attribute Recognition

Roshanak Zakizadeh·Yu Qian·Michele Sasdelli·Eduard Vazquez
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Abstract

In this paper, we present a method for instance ranking and retrieval at fine-grained level based on the global features extracted from a multi-attribute recognition model which is not dependent on landmarks information or part-based annotations. Further, we make this architecture suitable for mobile-device application by adopting the bilinear CNN to make the multi-attribute recognition model smaller (in terms of the number of parameters). The experiments run on the Dress category of DeepFashion In-Shop Clothes Retrieval and CUB200 datasets show that the results of instance retrieval at fine-grained level are promising for these datasets, specially in terms of texture and color.

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Roshanak Zakizadeh, Yu Qian, Michele Sasdelli, Eduard Vazquez. 2018-11-07. Instance Retrieval at Fine-grained Level Using Multi-Attribute Recognition. https://arxiv.org/abs/1811.02949

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