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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/filipgdorm/binary_range_maps

공식 코드

Generating Binary Species Range Maps

https://github.com/giangnguyen2412/PCNN-src-code-TMRL2024

공식 코드

PCNN: Probable-Class Nearest-Neighbor Explanations Improve Fine-Grained Image Classification Accuracy for AIs and Humans

https://github.com/github-songsong/fine-grained-pointcloud-object-dataset

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Enhancing Fine-Grained 3D Object Recognition using Hybrid Multi-Modal Vision Transformer-CNN Models

https://github.com/google-research/big_transfer

공식 코드

Big Transfer (BiT): General Visual Representation Learning

https://github.com/google-research/google-research/tree/master/muNet

공식 코드

An Evolutionary Approach to Dynamic Introduction of Tasks in Large-scale Multitask Learning Systems

https://github.com/google-research/sam

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Sharpness-Aware Minimization for Efficiently Improving Generalization

https://github.com/google-research/vision_transformer

공식 코드

An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

https://github.com/google/goldfinch

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The Unreasonable Effectiveness of Noisy Data for Fine-Grained Recognition

https://github.com/guoyurong0104/crl-code

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Competing Ratio Loss for Discriminative Multi-class Image Classification

https://github.com/huawei-noah/CV-Backbones/tree/master/tnt_pytorch

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Transformer in Transformer

https://github.com/huawei-noah/CV-backbones

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Transformer in Transformer

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

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DenseNets Reloaded: Paradigm Shift Beyond ResNets and ViTs

https://github.com/human-analysis/neural-architecture-transfer

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Neural Architecture Transfer

https://github.com/hyao1/ecc

공식 코드

Exploration of Class Center for Fine-Grained Visual Classification

https://github.com/iamhankai/attribute-aware-attention

공식 코드

Attribute-Aware Attention Model for Fine-grained Representation Learning

https://github.com/icvteam/part

공식 코드

Part-guided Relational Transformers for Fine-grained Visual Recognition

https://github.com/imageomics/intr

공식 코드

A Simple Interpretable Transformer for Fine-Grained Image Classification and Analysis

https://github.com/jayrothenberger/meta-co-training

공식 코드

Meta Co-Training: Two Views are Better than One

https://github.com/jiakangyuan/helixformer

공식 코드

Learning Cross-Image Object Semantic Relation in Transformer for Few-Shot Fine-Grained Image Classification

https://github.com/jiangtaoxie/fast-MPN-COV

공식 코드

Towards Faster Training of Global Covariance Pooling Networks by Iterative Matrix Square Root Normalization

https://github.com/jieshibo/tocom

공식 코드

Token Compensator: Altering Inference Cost of Vision Transformer without Re-Tuning

https://github.com/jpeginspireddl/jpeg-inspired-dl

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JPEG Inspired Deep Learning

https://github.com/kai-wen-yang/qvix

공식 코드

Good Questions Help Zero-Shot Image Reasoning

https://github.com/kmbmjn/DropoutCorrectly

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How to Use Dropout Correctly on Residual Networks with Batch Normalization

https://github.com/kmbmjn/GaussianAttentionBias

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Understanding Gaussian Attention Bias of Vision Transformers Using Effective Receptive Fields

https://github.com/kmbmjn/deadpixeltest_code

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Dead Pixel Test Using Effective Receptive Field

https://github.com/lanfeng4659/knowledgeminingwithscenetext

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Knowledge Mining with Scene Text for Fine-Grained Recognition

https://github.com/layumi/Person-reID_GAN

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Unlabeled Samples Generated by GAN Improve the Person Re-identification Baseline in vitro

https://github.com/liuziyu77/visual-rft

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Visual-RFT: Visual Reinforcement Fine-Tuning

https://github.com/mahdi-darvish/gans-augmented-pet-classifier

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Towards Fine-grained Image Classification with Generative Adversarial Networks and Facial Landmark Detection

https://github.com/mahuanaaa/intta

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Spurious Feature Eraser: Stabilizing Test-Time Adaptation for Vision-Language Foundation Model

https://github.com/microsoft/AutoML

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AutoFormer: Searching Transformers for Visual Recognition

https://github.com/moiexpositoalonsolab/DivShift

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DivShift: Exploring Domain-Specific Distribution Shifts in Large-Scale, Volunteer-Collected Biodiversity Datasets

https://github.com/mrT23/TResNet

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TResNet: High Performance GPU-Dedicated Architecture

https://github.com/mv-lab/ViT-FGVC8

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Exploring Vision Transformers for Fine-grained Classification

https://github.com/mvrl/birdsat

공식 코드

BirdSAT: Cross-View Contrastive Masked Autoencoders for Bird Species Classification and Mapping

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