SwinFG: A fine-grained recognition scheme based on swin transformer

Z Ma, X Wu, A Chu, L Huang, Z Wei - Expert Systems with Applications, 2024 - Elsevier
Fine-grained image recognition (FGIR) is a challenging task as it requires the recognition of
sub-categories with subtle differences. Recently, the swin transformer has shown impressive …

Transfg: A transformer architecture for fine-grained recognition

J He, JN Chen, S Liu, A Kortylewski, C Yang… - Proceedings of the …, 2022 - ojs.aaai.org
Fine-grained visual classification (FGVC) which aims at recognizing objects from
subcategories is a very challenging task due to the inherently subtle inter-class differences …

TransIFC: Invariant cues-aware feature concentration learning for efficient fine-grained bird image classification

H Liu, C Zhang, Y Deng, B Xie, T Liu… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Fine-grained bird image classification (FBIC) is not only meaningful for endangered bird
observation and protection but also a prevalent task for image classification in multimedia …

Denoising vision transformers

J Yang, KZ Luo, J Li, C Deng, L Guibas… - … on Computer Vision, 2025 - Springer
We study a crucial yet often overlooked issue inherent to Vision Transformers (ViTs): feature
maps of these models exhibit grid-like artifacts (“Original features” in Fig. 1), which hurt the …

[HTML][HTML] Towards a multisensor station for automated biodiversity monitoring

JW Wägele, P Bodesheim, SJ Bourlat, J Denzler… - Basic and Applied …, 2022 - Elsevier
Rapid changes of the biosphere observed in recent years are caused by both small and
large scale drivers, like shifts in temperature, transformations in land-use, or changes in the …

Fine-grained visual classification via internal ensemble learning transformer

Q Xu, J Wang, B Jiang, B Luo - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Recently, vision transformers (ViTs) have been investigated in fine-grained visual
recognition (FGVC) and are now considered state of the art. However, most ViT-based works …

SR-GNN: Spatial Relation-Aware Graph Neural Network for Fine-Grained Image Categorization

A Bera, Z Wharton, Y Liu, N Bessis… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Over the past few years, a significant progress has been made in deep convolutional neural
networks (CNNs)-based image recognition. This is mainly due to the strong ability of such …

Granularity-aware distillation and structure modeling region proposal network for fine-grained image classification

X Ke, Y Cai, B Chen, H Liu, W Guo - Pattern Recognition, 2023 - Elsevier
Fine-grained visual classification (FGVC) aims to identify objects belonging to multiple sub-
categories of the same super-category. The key to solving fine-grained classification …

A novel plug-in module for fine-grained visual classification

PY Chou, CH Lin, WC Kao - arXiv preprint arXiv:2202.03822, 2022 - arxiv.org
Visual classification can be divided into coarse-grained and fine-grained classification.
Coarse-grained classification represents categories with a large degree of dissimilarity, such …

Re-rank coarse classification with local region enhanced features for fine-grained image recognition

S Yang, S Liu, C Yang, C Wang - arXiv preprint arXiv:2102.09875, 2021 - arxiv.org
Fine-grained image recognition is very challenging due to the difficulty of capturing both
semantic global features and discriminative local features. Meanwhile, these two features …