Densifying Supervision for Fine-Grained Visual Comparisons

International Journal of Computer Vision, pp. 2704-2730, 2020.

Cited by: 0|Bibtex|Views7|DOI:https://doi.org/10.1007/s11263-020-01344-9
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Abstract:

Detecting subtle differences in visual attributes requires inferring which of two images exhibits a property more, e.g., which face is smiling slightly more, or which shoe is slightly more sporty. While valuable for applications ranging from biometrics to online shopping, fine-grained attributes are challenging to learn. Unlike traditiona...More

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