In this paper, we propose Long-Tail Hashing Network (LTHNet), a novel two-stage deep hashing approach that addresses the problem of learning to hash for more ...
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Hashing, which represents data items as compact binary codes, has been becoming a more and more popular technique, e.g., for large-scale image retrieval, ...
Nov 28, 2022 · Several long-tail hashing methods have been proposed but they can not adapt for multi-modal data, due to the complex interplay between labels ...
Several long- tail hashing methods have been proposed but they can not adapt for multi-modal data, due to the complex interplay between labels and individuality ...
Long-Tail Hashing (Learning to hash from more realistic long-tail datasets), SIGIR 2021, CCF A类. - butterfly-chinese/long-tail-hashing.
Jul 15, 2021 · that addresses the problem of learning to hash for more realistic datasets where the data labels roughly exhibit a long-tail distri- bution.
A key problem of long-tailed hashing is the information loss caused by dimension reduction operation, witch will make hash codes less discriminative. In ...
A novel two-stage deep hashing approach that addresses the problem of learning to hash for more realistic datasets where the data labels roughly exhibit a ...
Feb 7, 2023 · Several long-tail hashing methods have been proposed but they can not adapt for multi-modal data, due to the complex interplay between labels ...
Nov 7, 2021 · In this paper, we introduce a meta-learning based cross-modal hashing method (MetaCMH) to handle long-tailed data.