SOTAVerified

Image Classification

Image Classification is a fundamental task in vision recognition that aims to understand and categorize an image as a whole under a specific label. Unlike object detection, which involves classification and location of multiple objects within an image, image classification typically pertains to single-object images. When the classification becomes highly detailed or reaches instance-level, it is often referred to as image retrieval, which also involves finding similar images in a large database.

Source: Metamorphic Testing for Object Detection Systems

Papers

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Showing 951–1000 of 10419 papers

TitleStatusHype
Content-aware Token Sharing for Efficient Semantic Segmentation with Vision TransformersCode1
Automated detection of COVID-19 cases from chest X-ray images using deep neural network and XGBoostCode1
Gradient Surgery for Multi-Task LearningCode1
GradInit: Learning to Initialize Neural Networks for Stable and Efficient TrainingCode1
AASAE: Augmentation-Augmented Stochastic AutoencodersCode1
Graph Attention Transformer Network for Multi-Label Image ClassificationCode1
AQD: Towards Accurate Fully-Quantized Object DetectionCode1
Graph Convolutions Enrich the Self-Attention in Transformers!Code1
Learning Hierarchical Image Segmentation For Recognition and By RecognitionCode1
Adversarial Robustness on In- and Out-Distribution Improves ExplainabilityCode1
Concept Learners for Few-Shot LearningCode1
Group Fisher Pruning for Practical Network CompressionCode1
Concurrent Spatial and Channel Squeeze & Excitation in Fully Convolutional NetworksCode1
Automated Relational Meta-learningCode1
All-in-One Image Coding for Joint Human-Machine Vision with Multi-Path AggregationCode1
Automatically designing CNN architectures using genetic algorithm for image classificationCode1
Arch-Net: Model Distillation for Architecture Agnostic Model DeploymentCode1
Hard Sample Aware Noise Robust Learning for Histopathology Image ClassificationCode1
Harmonic Convolutional Networks based on Discrete Cosine TransformCode1
Harmonic Networks with Limited Training SamplesCode1
Head Network Distillation: Splitting Distilled Deep Neural Networks for Resource-Constrained Edge Computing SystemsCode1
Heavy Ball Neural Ordinary Differential EquationsCode1
Compressing Features for Learning with Noisy LabelsCode1
Heuristic Hyperparameter Optimization for Convolutional Neural Networks using Genetic AlgorithmCode1
Are Natural Domain Foundation Models Useful for Medical Image Classification?Code1
Automatic Recognition of Abdominal Organs in Ultrasound Images based on Deep Neural Networks and K-Nearest-Neighbor ClassificationCode1
Hire-MLP: Vision MLP via Hierarchical RearrangementCode1
Histopathological Image Classification with Cell Morphology Aware Deep Neural NetworksCode1
Compressive Visual RepresentationsCode1
How Does Pruning Impact Long-Tailed Multi-Label Medical Image Classifiers?Code1
How to Combine Variational Bayesian Networks in Federated LearningCode1
Are These Birds Similar: Learning Branched Networks for Fine-grained RepresentationsCode1
How to train your ViT? Data, Augmentation, and Regularization in Vision TransformersCode1
How Well Do Self-Supervised Models Transfer?Code1
HRN: A Holistic Approach to One Class LearningCode1
HR-NAS: Searching Efficient High-Resolution Neural Architectures with Lightweight TransformersCode1
HVT: A Comprehensive Vision Framework for Learning in Non-Euclidean SpaceCode1
Hyperbolic Contrastive Learning for Visual Representations beyond ObjectsCode1
Hyperbolic Image EmbeddingsCode1
Can We Talk Models Into Seeing the World Differently?Code1
Spatial and Spatial-Spectral Morphological Mamba for Hyperspectral Image ClassificationCode1
Automating Continual LearningCode1
Hyperspectral Image Classification Using Deep Matrix CapsulesCode1
Hyperspectral Image Classification with Attention Aided CNNsCode1
CondenseNet V2: Sparse Feature Reactivation for Deep NetworksCode1
iDAT: inverse Distillation Adapter-TuningCode1
A Fast 3D CNN for Hyperspectral Image ClassificationCode1
Image and Text fusion for UPMC Food-101 \ BERT and CNNsCode1
Image Classification With Small Datasets: Overview and BenchmarkCode1
Contrasting Intra-Modal and Ranking Cross-Modal Hard Negatives to Enhance Visio-Linguistic Compositional UnderstandingCode1
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All datasetsImageNetCIFAR-10CIFAR-100STL-10ObjectNetMNISTSVHNiNaturalist 2018ImageNet ReaLFlowers-102Clothing1Mmini WebVision 1.0

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CoCa (finetuned)Top 1 Accuracy91—Unverified
2Model soups (BASIC-L)Top 1 Accuracy90.98—Unverified
3Model soups (ViT-G/14)Top 1 Accuracy90.94—Unverified
4DaViT-GTop 1 Accuracy90.4—Unverified
5DaViT-HTop 1 Accuracy90.2—Unverified
6Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2—Unverified
7SwinV2-GTop 1 Accuracy90.17—Unverified
8MAWS (ViT-6.5B)Top 1 Accuracy90.1—Unverified
9Florence-CoSwin-HTop 1 Accuracy90.05—Unverified
10Meta Pseudo Labels (EfficientNet-B6-Wide)Top 1 Accuracy90—Unverified