Fine-grained image analysis with deep learning: A survey

XS Wei, YZ Song, O Mac Aodha, J Wu… - IEEE transactions on …, 2021 - ieeexplore.ieee.org
Fine-grained image analysis (FGIA) is a longstanding and fundamental problem in computer
vision and pattern recognition, and underpins a diverse set of real-world applications. The …

Attribute-aware deep hashing with self-consistency for large-scale fine-grained image retrieval

XS Wei, Y Shen, X Sun, P Wang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Our work focuses on tackling large-scale fine-grained image retrieval as ranking the images
depicting the concept of interests (ie, the same sub-category labels) highest based on the …

Multi-scale fine-grained alignments for image and sentence matching

W Li, Y Wang, Y Su, X Li, AA Liu… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Image and sentence matching is a critical task to bridge the visual and textual discrepancy
due to the heterogeneous modalities. Great progress has been made by exploring the …

A-Net: Learning Attribute-Aware Hash Codes for Large-Scale Fine-Grained Image Retrieval

XS Wei, Y Shen, X Sun, HJ Ye… - Advances in Neural …, 2021 - proceedings.neurips.cc
Our work focuses on tackling large-scale fine-grained image retrieval as ranking the images
depicting the concept of interests (ie, the same sub-category labels) highest based on the …

Sub-region localized hashing for fine-grained image retrieval

X Xiang, Y Zhang, L Jin, Z Li… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Fine-grained image hashing is challenging due to the difficulties of capturing discriminative
local information to generate hash codes. On the one hand, existing methods usually extract …

A Survey on Fashion Image Retrieval

SM Islam, S Joardar, AA Sekh* - ACM Computing Surveys, 2024 - dl.acm.org
Fashion is the manner in which we introduce ourselves to the world and has become
perhaps the biggest industry on the planet. In recent years, fashion-related research has …

Deep progressive asymmetric quantization based on causal intervention for fine-grained image retrieval

L Ma, H Hong, F Meng, Q Wu… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
In the field of computer vision, fine-grained image retrieval is an extremely challenging task
due to the inherently subtle intra-class object variations. In addition, the high-dimensional …

Deep hash distillation for image retrieval

YK Jang, G Gu, B Ko, I Kang, NI Cho - European Conference on Computer …, 2022 - Springer
In hash-based image retrieval systems, degraded or transformed inputs usually generate
different codes from the original, deteriorating the retrieval accuracy. To mitigate this issue …

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 …

Dual-stream knowledge-preserving hashing for unsupervised video retrieval

P Li, H Xie, J Ge, L Zhang, S Min, Y Zhang - European Conference on …, 2022 - Springer
Unsupervised video hashing usually optimizes binary codes by learning to reconstruct input
videos. Such reconstruction constraint spends much effort on frame-level temporal context …