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Found 3 papers, 1 papers with code
Instance Retrieval at Fine-grained Level Using Multi-Attribute Recognition
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.
Improving the Annotation of DeepFashion Images for Fine-grained Attribute Recognition
After selecting categories with sufficient number of images for training, we remove very scarce attributes and merge the duplicate ones in each category, then we clean the dataset based on the new list of attributes.
FineTag: Multi-attribute Classification at Fine-grained Level in Images
In this paper, we address the extraction of the fine-grained attributes of an instance as a `multi-attribute classification' problem.
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