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Fine-Grained Image Classification

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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/naver-ai/dtm

공식 코드

Morphing Tokens Draw Strong Masked Image Models

https://github.com/naver-ai/lut

공식 코드

Learning with Unmasked Tokens Drives Stronger Vision Learners

https://github.com/naver-ai/rdnet

공식 코드

DenseNets Reloaded: Paradigm Shift Beyond ResNets and ViTs

https://github.com/njuyued/soc4ss-fgvc

공식 코드

Roll With the Punches: Expansion and Shrinkage of Soft Label Selection for Semi-supervised Fine-Grained Learning

https://github.com/picekl/DanishFungiDataset

공식 코드

Danish Fungi 2020 -- Not Just Another Image Recognition Dataset

https://github.com/pku-icst-mipl/sim-trans_acmmm2022

공식 코드

SIM-Trans: Structure Information Modeling Transformer for Fine-grained Visual Categorization

https://github.com/praveenchopra/ProgressiveSpinalNet

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ProgressiveSpinalNet architecture for FC layers

https://github.com/pris-cv/afgr

공식 코드

Multi-View Active Fine-Grained Recognition

https://github.com/pris-cv/bi-frn

공식 코드

Bi-directional Feature Reconstruction Network for Fine-Grained Few-Shot Image Classification

https://github.com/pris-cv/making-a-bird-ai-expert-work-for-you-and-me

공식 코드

Making a Bird AI Expert Work for You and Me

https://github.com/pris-cv/relmatch

공식 코드

Clue Me In: Semi-Supervised FGVC with Out-of-Distribution Data

https://github.com/raoyongming/CAL

공식 코드

Counterfactual Attention Learning for Fine-Grained Visual Categorization and Re-identification

https://github.com/raphael-baena/FIERCE-repo

공식 코드

Preserving Fine-Grain Feature Information in Classification via Entropic Regularization

https://github.com/researchmm/tasn

공식 코드

Looking for the Devil in the Details: Learning Trilinear Attention Sampling Network for Fine-grained Image Recognition

https://github.com/rush2406/Self-Supervised-Learning-for-Fine-grained-Image-Classification

공식 코드

Self-Supervised Learning for Fine-Grained Image Classification

https://github.com/rwightman/pytorch-image-models

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TResNet: High Performance GPU-Dedicated Architecture

https://github.com/saehyung-lee/dcc

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Dataset Condensation with Contrastive Signals

https://github.com/savadikarc/gift

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Generative Parameter-Efficient Fine-Tuning

https://github.com/shijxcs/lift

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Long-Tail Learning with Foundation Model: Heavy Fine-Tuning Hurts

https://github.com/sipkatom/The-Hitchhiker-s-Guide-to-Prior-Shift-Adaptation

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The Hitchhiker's Guide to Prior-Shift Adaptation

https://github.com/snap-stanford/comet

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Concept Learners for Few-Shot Learning

https://github.com/spraise/BSNet

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BSNet: Bi-Similarity Network for Few-shot Fine-grained Image Classification

https://github.com/tensorflow/models

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AutoAugment: Learning Augmentation Policies from Data

https://github.com/tensorflow/tpu/tree/master/models/official/efficientnet

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EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks

https://github.com/thomasnorr/q-senn

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Take 5: Interpretable Image Classification with a Handful of Features

https://github.com/tjddus9597/Proxy-Anchor-CVPR2020

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Proxy Anchor Loss for Deep Metric Learning

https://github.com/tristangomez44/br_npa

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BR-NPA: A Non-Parametric High-Resolution Attention Model to improve the Interpretability of Attention

https://github.com/vaishnavmohit/Conviformer

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Conviformers: Convolutionally guided Vision Transformer

https://github.com/visipedia/fg_geo

공식 코드

Geo-Aware Networks for Fine-Grained Recognition

https://github.com/wangguanan/denoiserep

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DenoiseRep: Denoising Model for Representation Learning

https://github.com/wvuvl/DARMA

공식 코드

Fine-Grained Visual Classification of Plant Species In The Wild: Object Detection as A Reinforced Means of Attention

https://github.com/xinyulyu/fgpl

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Fine-Grained Predicates Learning for Scene Graph Generation

https://github.com/xl-h/guie-2nd-place-solution

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2nd Place Solution to Google Universal Image Embedding

https://github.com/yangze0930/NTS-Net

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Learning to Navigate for Fine-grained Classification

https://github.com/yaolinli/idc

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Image Difference Captioning with Pre-training and Contrastive Learning

https://github.com/yaorong0921/cub-gha

공식 코드

Human Attention in Fine-grained Classification

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