Fine-Grained Image Recognition

Benchmarks archive 2025-07-28

4 leaderboard tables shown for this task, 4 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

12 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

30 shown of 39 papers with code (72 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Multi-branch and Multi-scale Attention Learning for Fine-Grained Visual Categorization
  20 Mar 2020 6 repositories listed
  Therefore, our multi-branch and multi-scale learning network(MMAL-Net) has good classification ability and robustness for images of different scales.
• Towards Faster Training of Global Covariance Pooling Networks by Iterative Matrix Square Root Normalization
  4 Dec 2017 4 repositories listed Syntology ran 3 of 3 samples · 0 unverified · 1 pointer-only (licence)
  Towards addressing this problem, we propose an iterative matrix square root normalization method for fast end-to-end training of global covariance pooling networks.
• Learning Multi-Attention Convolutional Neural Network for Fine-Grained Image Recognition
  1 Oct 2017 3 repositories listed
  Two losses are proposed to guide the multi-task learning of channel grouping and part classification, which encourages MA-CNN to generate more discriminative parts from feature channels and learn better fine-grained…
• Hawkeye: A PyTorch-based Library for Fine-Grained Image Recognition with Deep Learning
  14 Oct 2023 2 repositories listed
  However, the absence of a unified open-source software library covering various paradigms in FGIR poses a significant challenge for researchers and practitioners in the field.
• PaLI-X: On Scaling up a Multilingual Vision and Language Model
  29 May 2023 2 repositories listed Syntology ran 6 of 7 samples · 1 unverified
  We present the training recipe and results of scaling up PaLI-X, a multilingual vision and language model, both in terms of size of the components and the breadth of its training task mixture.
• Open-domain Visual Entity Recognition: Towards Recognizing Millions of Wikipedia Entities
  22 Feb 2023 2 repositories listed Syntology ran 1 of 4 samples · 3 unverified
  Large-scale multi-modal pre-training models such as CLIP and PaLI exhibit strong generalization on various visual domains and tasks.
• Local Patch AutoAugment with Multi-Agent Collaboration
  20 Mar 2021 2 repositories listed
  We formulate it as a multi-agent reinforcement learning (MARL) problem, where each agent learns an augmentation policy for each patch based on its content together with the semantics of the whole image.
• Destruction and Construction Learning for Fine-Grained Image Recognition
  1 Jun 2019 2 repositories listed
  In this paper, we propose a novel "Destruction and Construction Learning" (DCL) method to enhance the difficulty of fine-grained recognition and exercise the classification model to acquire expert knowledge.
• Cross-Layer Cache Aggregation for Token Reduction in Ultra-Fine-Grained Image Recognition
  31 Dec 2024 1 repository listed
  Ultra-fine-grained image recognition (UFGIR) is a challenging task that involves classifying images within a macro-category.
• Down-Sampling Inter-Layer Adapter for Parameter and Computation Efficient Ultra-Fine-Grained Image Recognition
  17 Sep 2024 1 repository listed
  Ultra-fine-grained image recognition (UFGIR) categorizes objects with extremely small differences between classes, such as distinguishing between cultivars within the same species, as opposed to species-level…
• Enhancing Fine-Grained Visual Recognition in the Low-Data Regime Through Feature Magnitude Regularization
  3 Sep 2024 1 repository listed
  Moreover, in the context of building FGVR models with limited data, these irrelevant features can dominate the training process, overshadowing more useful, generalizable discriminative features.
• Global-Local Similarity for Efficient Fine-Grained Image Recognition with Vision Transformers
  17 Jul 2024 1 repository listed
  Fine-grained recognition involves the classification of images from subordinate macro-categories, and it is challenging due to small inter-class differences.
• Res-VMamba: Fine-Grained Food Category Visual Classification Using Selective State Space Models with Deep Residual Learning
  24 Feb 2024 1 repository listed Syntology ran 3 of 3 samples · 0 unverified · 3 pointer-only (licence)
  Our findings elucidate that our proposed methodology establishes a new benchmark for SOTA performance in food recognition on the CNFOOD-241 dataset.
• Fine-grained Recognition with Learnable Semantic Data Augmentation
  1 Sep 2023 1 repository listed Syntology ran 3 of 7 samples · 4 unverified · 7 pointer-only (licence)
  Since images belonging to the same meta-category usually share similar visual appearances, mining discriminative visual cues is the key to distinguishing fine-grained categories.
• PPL: Pairwise Prototype Learning for Masked Face Recognition
  21 Nov 2022 1 repository listed
  Although the previously proposed method of using both face data without facemasks and those with synthesised facemasks for training improved the recognition performance, a certain drop in the recognition performance for…
• Taxonomy and evolution predicting using deep learning in images
  28 Jun 2022 1 repository listed
  Molecular and morphological characters, as important parts of biological taxonomy, are contradictory but need to be integrated.
• Making Heads or Tails: Towards Semantically Consistent Visual Counterfactuals
  24 Mar 2022 1 repository listed Syntology ran 1 of 4 samples · 3 unverified · 4 pointer-only (licence)
  A visual counterfactual explanation replaces image regions in a query image with regions from a distractor image such that the system's decision on the transformed image changes to the distractor class.
• A Novel Plug-in Module for Fine-Grained Visual Classification
  8 Feb 2022 1 repository listed
  Visual classification can be divided into coarse-grained and fine-grained classification.
• High-Order-Interaction for weakly supervised Fine-Grained Visual Categorization
  13 Nov 2021 1 repository listed
  Of those, methods based on bilinear pooling are one of the main categories for computing the interaction between deep features and have shown high effectiveness.
• The Curious Layperson: Fine-Grained Image Recognition without Expert Labels
  5 Nov 2021 1 repository listed
  We then train a fine-grained textual similarity model that matches image descriptions with documents on a sentence-level basis.
• Attend and Guide (AG-Net): A Keypoints-driven Attention-based Deep Network for Image Recognition
  23 Oct 2021 1 repository listed
  We address this by proposing an end-to-end CNN model, which learns meaningful features linking fine-grained changes using our novel attention mechanism.
• Fine-grained Hand Gesture Recognition in Multi-viewpoint Hand Hygiene
  7 Sep 2021 1 repository listed
  This paper contributes a new high-quality dataset for hand gesture recognition in hand hygiene systems, named "MFH".
• Counterfactual Attention Learning for Fine-Grained Visual Categorization and Re-identification
  19 Aug 2021 1 repository listed Syntology ran 8 of 11 samples · 3 unverified
  Unlike most existing methods that learn visual attention based on conventional likelihood, we propose to learn the attention with counterfactual causality, which provides a tool to measure the attention quality and a…
• Exploring Localization for Self-supervised Fine-grained Contrastive Learning
  30 Jun 2021 1 repository listed
  Self-supervised contrastive learning has demonstrated great potential in learning visual representations.
• Danish Fungi 2020 -- Not Just Another Image Recognition Dataset
  18 Mar 2021 1 repository listed
  Interestingly, ViT achieves results superior to CNN baselines with 80.
• Neural Prototype Trees for Interpretable Fine-grained Image Recognition
  3 Dec 2020 1 repository listed
  We propose the Neural Prototype Tree (ProtoTree), an intrinsically interpretable deep learning method for fine-grained image recognition.
• How Well Do Self-Supervised Models Transfer?
  26 Nov 2020 1 repository listed Syntology ran 4 of 5 samples · 1 unverified
  We evaluate the transfer performance of 13 top self-supervised models on 40 downstream tasks, including many-shot and few-shot recognition, object detection, and dense prediction.
• Contrastively-reinforced Attention Convolutional Neural Network for Fine-grained Image Recognition
  8 Sep 2020 1 repository listed
  The evaluation information is backpropagated and forces the classification stream to improve its awareness of visual attention, which helps classification.
• Semi-Supervised Recognition under a Noisy and Fine-grained Dataset
  18 Jun 2020 1 repository listed
  One of the difficulties of this competition is how to use unlabeled data.
• ePillID Dataset: A Low-Shot Fine-Grained Benchmark for Pill Identification
  28 May 2020 1 repository listed
  Identifying prescription medications is a frequent task for patients and medical professionals; however, this is an error-prone task as many pills have similar appearances (e.

Syntology lines on 8 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.