A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf
.
Mask-Guided Feature Extraction and Augmentation for Ultra-Fine-Grained Visual Categorization
2021
2021 Digital Image Computing: Techniques and Applications (DICTA)
While the fine-grained visual categorization (FGVC) problems have been greatly developed in the past years, the Ultrafine-grained visual categorization (Ultra-FGVC) problems have been understudied. FGVC aims at classifying objects from the same species (very similar categories), while the Ultra-FGVC targets at more challenging problems of classifying images at an ultra-fine granularity where even human experts may fail to identify the visual difference. The challenges for Ultra-FGVC mainly
doi:10.1109/dicta52665.2021.9647389
fatcat:2trqrkh4njcfplgslbqyjv37re