Contrastive masked autoencoders for self-supervised video hashing

Y Wang, J Wang, B Chen, Z Zeng, ST **a - Proceedings of the AAAI …, 2023‏ - ojs.aaai.org
Abstract Self-Supervised Video Hashing (SSVH) models learn to generate short binary
representations for videos without ground-truth supervision, facilitating large-scale video …

SEMICON: A learning-to-hash solution for large-scale fine-grained image retrieval

Y Shen, X Sun, XS Wei, QY Jiang, J Yang - European conference on …, 2022‏ - Springer
In this paper, we propose S uppression-E nhancing M ask based attention and I nteractive C
hannel transformati ON (SEMICON) to learn binary hash codes for dealing with large-scale …

Deep global semantic structure-preserving hashing via corrective triplet loss for remote sensing image retrieval

H Zhou, Q Qin, J Hou, J Dai, L Huang… - Expert Systems with …, 2024‏ - Elsevier
With the explosive increase of remote sensing data, how to search for remote sensing data
quickly and accurately in a vast dataset is an incredibly critical matter for research subjects …

Logit variated product quantization based on parts interaction and metric learning with knowledge distillation for fine-grained image retrieval

L Ma, X Luo, H Hong, F Meng… - IEEE Transactions on …, 2024‏ - ieeexplore.ieee.org
Image retrieval with fine-grained categories is an extremely challenging task due to the high
intraclass variance and low interclass variance. Most previous works have focused on …

Implementation Of The Swin Transformer and Its Application In Image Classification

RA Dihin, EN Al Shemmary, WAM Al-Jawher - Journal Port Science …, 2023‏ - jport.co
Implementation Of The Swin Transformer and Its Application In Image Classification Page 1
Rasha. A. Dihin, Ebtesam N. Al Shemmary, Waleed Ameen Al Jawher, 2023. Implementation …

ConceptHash: Interpretable Fine-Grained Hashing via Concept Discovery

KW Ng, X Zhu, YZ Song… - Proceedings of the IEEE …, 2024‏ - openaccess.thecvf.com
Existing fine-grained hashing methods typically lack code interpretability as they compute
hash code bits holistically using both global and local features. To address this limitation we …

ViTH-RFG: Vision transformer hashing with residual fuzzy generation for targeted attack in medical image retrieval

W Ding, C Liu, J Huang, C Cheng… - IEEE Transactions on …, 2023‏ - ieeexplore.ieee.org
The rapid advancement of medical technology has led to an exponential increase in the
volume of medical images. To optimize clinical practice, physicians often require efficient …

[PDF][PDF] Hugs Are Better Than Handshakes: Unsupervised Cross-Modal Transformer Hashing with Multi-granularity Alignment.

J Wang, Z Zeng, B Chen, Y Wang, D Liao, G Li… - BMVC, 2022‏ - bmvc2022.mpi-inf.mpg.de
The goal of unsupervised cross-modal hashing (UCMH) is to map different modalities into a
semantic-preserving hamming space without requiring label supervision. Existing deep …

Hugs bring double benefits: Unsupervised cross-modal hashing with multi-granularity aligned transformers

J Wang, Z Zeng, B Chen, Y Wang, D Liao, G Li… - International Journal of …, 2024‏ - Springer
Unsupervised cross-modal hashing (UCMH) has been commonly explored to support large-
scale cross-modal retrieval of unlabeled data. Despite promising progress, most existing …

Transitivity recovering decompositions: Interpretable and robust fine-grained relationships

A Chaudhuri, M Mancini, Z Akata… - Advances in Neural …, 2023‏ - proceedings.neurips.cc
Recent advances in fine-grained representation learning leverage local-to-global
(emergent) relationships for achieving state-of-the-art results. The relational representations …