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Fine-Grained Image Classification

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보존된 평가 기록: 374

Fine-Grained Image Classification is a task in computer vision where the goal is to classify images into subcategories within a larger category. For example, classifying different species of birds or different types of flowers. This task is considered to be fine-grained because it requires the model to distinguish between subtle differences in visual appearance and patterns, making it more challenging than regular image classification tasks.

<span style="color:grey; opacity: 0.6">( Image credit: Looking for the Devil in the Details )</span>

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/2004-0813/hmdrn-main

공식 코드

Hierarchical Mask-Enhanced Dual Reconstruction Network for Few-Shot Fine-Grained Image Classification

https://github.com/AlexColagrande/MANO

공식 코드

Linear Attention with Global Context: A Multipole Attention Mechanism for Vision and Physics

https://github.com/Alibaba-MIIL/ImageNet21K

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ImageNet-21K Pretraining for the Masses

https://github.com/DiKorsch/deep_fve

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End-to-end Learning of a Fisher Vector Encoding for Part Features in Fine-grained Recognition

https://github.com/DreadPiratePsyopus/Fine_Grained_Clf

공식 코드

Fine-grained Image Classification and Retrieval by Combining Visual and Locally Pooled Textual Features

https://github.com/GKalliatakis/DisplaceNet

공식 코드

DisplaceNet: Recognising Displaced People from Images by Exploiting Dominance Level

https://github.com/HCPLab-SYSU/HSE

공식 코드

Fine-Grained Representation Learning and Recognition by Exploiting Hierarchical Semantic Embedding

https://github.com/JDAI-CV/LIO

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Look-into-Object: Self-supervised Structure Modeling for Object Recognition

https://github.com/KingJamesSong/DifferentiableSVD

공식 코드

On the Eigenvalues of Global Covariance Pooling for Fine-grained Visual Recognition

https://github.com/Markin-Wang/FFVT

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Feature Fusion Vision Transformer for Fine-Grained Visual Categorization

https://github.com/NUST-Machine-Intelligence-Laboratory/dmbfgvr

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Data-driven Meta-set Based Fine-Grained Visual Classification

https://github.com/NYU-DICE-Lab/open_clip

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LiT Tuned Models for Efficient Species Detection

https://github.com/Nandan91/ULSAM

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ULSAM: Ultra-Lightweight Subspace Attention Module for Compact Convolutional Neural Networks

https://github.com/PKU-ICST-MIPL/OPAM_TIP2018

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Object-Part Attention Model for Fine-grained Image Classification

https://github.com/PRIS-CV/Fine-Grained-or-Not

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Your "Flamingo" is My "Bird": Fine-Grained, or Not

https://github.com/PRIS-CV/PMG-Progressive-Multi-Granularity-Training

공식 코드

Fine-Grained Visual Classification via Progressive Multi-Granularity Training of Jigsaw Patches

https://github.com/RuoyiDu/PMG-Progressive-Multi-Granularity-Training

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Fine-Grained Visual Classification via Progressive Multi-Granularity Training of Jigsaw Patches

https://github.com/SHI-Labs/Compact-Transformers

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Escaping the Big Data Paradigm with Compact Transformers

https://github.com/Shaoli-Huang/SnapMix

공식 코드

SnapMix: Semantically Proportional Mixing for Augmenting Fine-grained Data

https://github.com/TACJu/TransFG

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TransFG: A Transformer Architecture for Fine-grained Recognition

https://github.com/TAMU-VITA/Focus-Longer-to-See-Better

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Focus Longer to See Better:Recursively Refined Attention for Fine-Grained Image Classification

https://github.com/TianshuXie/Cut-Thumbnail

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Cut-Thumbnail: A Novel Data Augmentation for Convolutional Neural Network

https://github.com/Westlake-AI/openmixup

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Exploring Localization for Self-supervised Fine-grained Contrastive Learning

https://github.com/XuyangSHEN/Non-binary-deep-transfer-learning-for-image-classification

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Non-binary deep transfer learning for image classification

https://github.com/YanghuiSong/DS_FusionNet

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DS_FusionNet: Dynamic Dual-Stream Fusion with Bidirectional Knowledge Distillation for Plant Disease Recognition

https://github.com/Yonghongwei/Gradient-Centralization

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Gradient Centralization: A New Optimization Technique for Deep Neural Networks

https://github.com/ZF1044404254/MMAL-Net

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Multi-branch and Multi-scale Attention Learning for Fine-Grained Visual Categorization

https://github.com/ZF1044404254/TBMSL-Net

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Multi-branch and Multi-scale Attention Learning for Fine-Grained Visual Categorization

https://github.com/ZhenyueQin/Research-Softmax-with-Mutual-Information

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Rethinking Softmax with Cross-Entropy: Neural Network Classifier as Mutual Information Estimator

https://github.com/abhimanyudubey/confusion

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Pairwise Confusion for Fine-Grained Visual Classification

https://github.com/aderonhuang/fgvc9_snakeclef2022

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Explored An Effective Methodology for Fine-Grained Snake Recognition

https://github.com/aioz-ai/sac

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Fine-Grained Visual Classification using Self Assessment Classifier

https://github.com/akonlau/dtrg

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Convolutional Fine-Grained Classification with Self-Supervised Target Relation Regularization

https://github.com/alibaba-miil/ml_decoder

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ML-Decoder: Scalable and Versatile Classification Head

https://github.com/ananthu-aniraj/masking_strategies_bias_removal

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Masking Strategies for Background Bias Removal in Computer Vision Models

https://github.com/ananthu-aniraj/pdiscoformer

공식 코드

PDiscoFormer: Relaxing Part Discovery Constraints with Vision Transformers

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.