[NeurIPS 2021] Official implementation of the paper "One Loss for All: Deep Hashing with a Single Cosine Similarity based Learning Objective"
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Updated
May 18, 2024 - Python
[NeurIPS 2021] Official implementation of the paper "One Loss for All: Deep Hashing with a Single Cosine Similarity based Learning Objective"
Fast Image Retrieval (FIRe) is an open source project to promote image retrieval research. It implements most of the major binary hashing methods to date, together with different popular backbone networks and public datasets.
Huei-Fang Yang, Cheng-Hao Tu, and Chu-Song Chen, "Adaptive Labeling for Hash Codes Learning via Neural Networks," IEEE International Conference on Image Processing, ICIP 2019, September 2019
Huei-Fang Yang, Kevin Lin, and Chu-Song Chen, "Supervised Learning of Semantics-Preserving Hash via Deep Convolutional Neural Networks," IEEE Transactions on Pattern Analysis and Machine Intelligence, volume 40(2), pages 437 - 451, February 2018
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