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Long-tail cross-modal hashing

Web18 de jul. de 2024 · Go Irie, Hiroyuki Arai, and Yukinobu Taniguchi. 2015. Alternating Co-Quantization for Cross-Modal Hashing. In IEEE International Conference on Computer Vision. 1886--1894. Google Scholar Digital Library; Qing-Yuan Jiang and Wu-Jun Li. 2016. Deep Cross-Modal Hashing. Computing Research Repository, Vol. abs/1602.02255 … WebMeta Cross-Modal Hashing on Long-Tailed Data ... (MetaCMH) based on meta learning for long-tail datasets. 2.2 Meta-learning To date, no single or general def-inition of meta …

Yongxin Wang (王永欣)

WebDue to the advantage of reducing storage while speeding up query time on big heterogeneous data, cross-modal hashing has been extensively studied for approximate nearest neighbor search of multi-modal data. Most hashing methods assume that training data is class-balanced. However, in practice, real world data often have a long-tailed … Weblong-tail hashing cannot be solved simply by reweighting different classes in the loss function, but the combination of extended dy-namic meta-embedding, cross-entropy … dehydrated peas https://codexuno.com

Semantic-rebased cross-modal hashing for scalable unsupervised …

Web5 de jun. de 2024 · Jian Zhang, Yuxin Peng, and Mingkuan Yuan. 2024b. SCH-GAN: Semi-supervised Cross-modal Hashing by Generative Adversarial Network. CoRR, Vol. abs/1802.02488 (2024). arxiv: 1802.02488 Google Scholar; Jian Zhang, Yuxin Peng, and Mingkuan Yuan. 2024c. Unsupervised Generative Adversarial Cross-Modal Hashing. In … WebExisting Cross Modal Hashing (CMH) methods are mainly designed for balanced data, while imbalanced data with long-tail distribution is more general in real-world. Several … Web26 de mai. de 2024 · In this paper, we study how to make unsupervised cross-modal hashing (CMH) benefit from contrastive learning (CL) by overcoming two challenges. To be exact, i) to address the performance degradation issue caused by binary optimization for hashing, we propose a novel momentum optimizer that performs hashing operation … dehydrated peas and corn

HashGAN:Attention-aware Deep Adversarial Hashing for Cross Modal ...

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Long-tail cross-modal hashing

Long-tail Cross Modal Hashing Papers With Code

Web7 de nov. de 2024 · Most hashing methods assume that training data is class-balanced.However, in practice, real world data often have a long-tailed distribution. In … Web28 de nov. de 2024 · Existing Cross Modal Hashing (CMH) methods are mainly designed for balanced data, while imbalanced data with long-tail distribution is more general in …

Long-tail cross-modal hashing

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Web7 de nov. de 2024 · Most hashing methods assume that training data is class-balanced.However, in practice, real world data often have a long-tailed distribution. In … WebCross-modal Hashing Jun Yu1*, Hao Zhou1, Yibing Zhan1, Dacheng Tao2 1 HangZhou Dianzi University 2 The University of Sydney [email protected], [email protected], [email protected], [email protected] Abstract Unsupervised cross-modal hashing (UCMH) has become a hot topic recently. Current UCMH focuses on exploring …

WebMost hashing methods assume that training data is class-balanced.However, in practice, real world data often have a long-tailed distribution. In this paper, we introduce a meta … WebIn Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 189 – 198. Google Scholar [84] Wang Yongxin, Chen Zhen-Duo, Luo Xin, and Xu Xin-Shun. 2024. High-dimensional sparse cross-modal hashing with fine-grained similarity embedding. In Proceedings of the Web Conference 2024. 2900 ...

WebHashing-based cross-modal search which aims to map multiple modality features into binary codes has attracted increasingly attention due to its storage and search efficiency especially in large-scale database retrieval. Recent unsupervised deep cross-modal hashing methods have shown promising results. However, existing approaches typically … Web11 de mai. de 2024 · Figure 1: Workflow of the proposed Rank based Deep Cross-Modal Hashing (RDCMH). RDCMH encompasses two steps: (1) an Image CNN network for learning image representations and a Text two-layer Network for learning text representations. (2) Jointly optimize the cross-modal triplet ranking loss and the …

Web2 de abr. de 2024 · Mask Cross-Modal Hashing Networks. Abstract: Due to the rapid development of deep learning, cross-modal retrieval has achieved significant progress in recent years. Moreover, cross-modal hashing has recently attracted considerable attention to multi-modal retrieval applications due to its advantages of low storage costs and fast …

Web18 de fev. de 2024 · Supervised cross-modal hashing has attracted much attention. However, there are still some challenges, e.g., how to effectively embed the label information into binary codes, how to avoid using a large similarity matrix and make a model scalable to large-scale datasets, how to efficiently solve the binary optimization problem. … fender style string-thru bass bridgeWebIn this paper, we propose Long-Tail Hashing Network ... Nonlinear Robust Discrete Hashing for Cross-Modal Retrieval. In SIGIR . 1349--1358. Google Scholar; Li Yuan, … fender subsonic baritone neckdehydrated pecan pie snacksWeb8 de abr. de 2024 · To this end, we propose a new framework, termed as Weakly Supervised Hashing with Reconstructive Cross-modal Attention (WSHRCA), to learn compact visual-semantic representation with more reliable ... dehydrated peas snackWebDeep Hashing with Minimal-Distance-Separated Hash Centers Liangdao Wang · Yan Pan · Cong Liu · Hanjiang Lai · Jian Yin · Ye Liu Few-Shot Learning with Visual Distribution … dehydrated pee chartWeb28 de nov. de 2024 · 11/28/22 - Existing Cross Modal Hashing (CMH) methods are mainly designed for balanced data, while imbalanced data with long-tail distributio... dehydrated pecansWebLong-tail Cross Modal Hashing Zijun Gao1, Jun Wang2,*, Guoxian Yu1,2, Zhongmin Yan1, Carlotta Domeniconi3, Jinglin Zhang4 1School of Software, Shandong University, … dehydrated pee sting