One Loss for All: Deep Hashing with a Single Cosine Similarity based Learning Objective

29 September 2021

Papers citing "One Loss for All: Deep Hashing with a Single Cosine Similarity based Learning Objective"

9 / 9 papers shown

Title
COMAE: COMprehensive Attribute Exploration for Zero-shot Hashing Yuqi Li Qingqing Long Yihang Zhou Yuchen Yan Xiao Luo Zeyu Dong Xuezhi Wang Zhen Meng Pengfei Wang VLM 49 3 0 26 Feb 2024
Attribute-Aware Deep Hashing with Self-Consistency for Large-Scale Fine-Grained Image Retrieval Xiu-Shen Wei Yang Shen Xuhao Sun Peng Wang Yuxin Peng 22 10 0 21 Nov 2023
Semantic-Aware Adversarial Training for Reliable Deep Hashing Retrieval Xu Yuan Zheng-Wei Zhang Xunguang Wang Lin Wu AAML 31 11 0 23 Oct 2023
Towards Efficient Deep Hashing Retrieval: Condensing Your Data via Feature-Embedding Matching Tao Feng Jie Zhang Peizheng Wang Zhijie Wang Shengyuan Pang DD 46 0 0 29 May 2023
MITFAS: Mutual Information based Temporal Feature Alignment and Sampling for Aerial Video Action Recognition Ruiqi Xian Xijun Wang Dinesh Manocha 21 10 0 05 Mar 2023
Unsupervised Hashing with Similarity Distribution Calibration KamWoh Ng Xiatian Zhu Jiun Tian Hoe Chee Seng Chan Tianyu Zhang Yi-Zhe Song Tao Xiang 26 2 0 15 Feb 2023
A Lower Bound of Hash Codes' Performance Xiaosu Zhu Jingkuan Song Yu Lei Lianli Gao Hengtao Shen 38 2 0 12 Oct 2022
SEMICON: A Learning-to-hash Solution for Large-scale Fine-grained Image Retrieval Yang Shen Xuhao Sun Xiu-Shen Wei Qing-Yuan Jiang Jian Yang 29 18 0 28 Sep 2022
Deep Hash Distillation for Image Retrieval Young Kyun Jang Geonmo Gu ByungSoo Ko Isaac Kang N. Cho 19 34 0 16 Dec 2021