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 3201–3250 of 10419 papers

TitleStatusHype
Visual Prompt Based Personalized Federated Learning—0
Knowledge Distillation from Single to Multi Labels: an Empirical StudyCode0
SMUG: Towards robust MRI reconstruction by smoothed unrollingCode0
A Contrastive Knowledge Transfer Framework for Model Compression and Transfer LearningCode0
Is forgetting less a good inductive bias for forward transfer?—0
Context Normalization Layer with Applications—0
Adversarial Attacks to Direct Data-driven Control for Destabilization—0
Twin Contrastive Learning with Noisy LabelsCode1
On Model Compression for Neural Networks: Framework, Algorithm, and Convergence GuaranteeCode0
The challenge of representation learning: Improved accuracy in deep vision models does not come with better predictions of perceptual similarity—0
A Test Statistic Estimation-based Approach for Establishing Self-interpretable CNN-based Binary Classifiers—0
Pretrained ViTs Yield Versatile Representations For Medical ImagesCode1
MSINet: Twins Contrastive Search of Multi-Scale Interaction for Object ReIDCode1
PMC-CLIP: Contrastive Language-Image Pre-training using Biomedical DocumentsCode2
Bag of Tricks with Quantized Convolutional Neural Networks for image classification—0
CrossFormer++: A Versatile Vision Transformer Hinging on Cross-scale AttentionCode2
FireRisk: A Remote Sensing Dataset for Fire Risk Assessment with Benchmarks Using Supervised and Self-supervised LearningCode1
RotoGBML: Towards Out-of-Distribution Generalization for Gradient-Based Meta-Learning—0
Adv-Bot: Realistic Adversarial Botnet Attacks against Network Intrusion Detection Systems—0
Extending global-local view alignment for self-supervised learning with remote sensing imageryCode1
Schema Inference for Interpretable Image ClassificationCode1
Endoscopy Classification Model Using Swin Transformer and Saliency Map—0
Stabilizing Transformer Training by Preventing Attention Entropy CollapseCode2
Distributionally Robust Optimization with Probabilistic GroupCode0
Optimizing Federated Learning for Medical Image Classification on Distributed Non-iid Datasets with Partial Labels—0
Uncertainty quantification in neural network classifiers -- a local linear approach—0
Variational Quantum Neural Networks (VQNNS) in Image Classification—0
AnoMalNet: Outlier Detection based Malaria Cell Image Classification Method Leveraging Deep Autoencoder—0
TAKT: Target-Aware Knowledge Transfer for Whole Slide Image ClassificationCode0
Understanding and Constructing Latent Modality Structures in Multi-modal Representation Learning—0
Spawrious: A Benchmark for Fine Control of Spurious Correlation BiasesCode1
NIFF: Alleviating Forgetting in Generalized Few-Shot Object Detection via Neural Instance Feature Forging—0
HyT-NAS: Hybrid Transformers Neural Architecture Search for Edge Devices—0
Robustness-preserving Lifelong Learning via Dataset Condensation—0
Hybrid quantum-classical convolutional neural network for phytoplankton classification—0
FFT-based Dynamic Token Mixer for VisionCode1
Towards Composable Distributions of Latent Space Augmentations—0
A Unified Algebraic Perspective on Lipschitz Neural NetworksCode1
DeepMAD: Mathematical Architecture Design for Deep Convolutional Neural Network—0
Graph-based Representation for Image based on Granular-ball—0
Demystifying What Code Summarization Models Learned—0
Fine-Grained ImageNet Classification in the WildCode0
Self-supervised Learning for Gastrointestinal Pathologies Endoscopy Image Classification with Triplet Loss—0
Structure Pretraining and Prompt Tuning for Knowledge Graph TransferCode1
Pyramid Pixel Context Adaption Network for Medical Image Classification with Supervised Contrastive Learning—0
Diagnosing Model Performance Under Distribution ShiftCode0
EcoTTA: Memory-Efficient Continual Test-time Adaptation via Self-distilled RegularizationCode1
Evaluation of Confidence-based Ensembling in Deep Learning Image Classification—0
Data-Efficient Training of CNNs and Transformers with Coresets: A Stability PerspectiveCode0
Spatio-Temporal Structure Consistency for Semi-supervised Medical Image Classification—0
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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
5Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2—Unverified
6DaViT-HTop 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
10RevCol-HTop 1 Accuracy90—Unverified