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 2051–2100 of 10419 papers

TitleStatusHype
Dirichlet-based Uncertainty Calibration for Active Domain AdaptationCode1
DiG-IN: Diffusion Guidance for Investigating Networks - Uncovering Classifier Differences Neuron Visualisations and Visual Counterfactual ExplanationsCode1
Diffusion Models Beat GANs on Image ClassificationCode1
Dilated convolution with learnable spacingsCode1
On Creating Benchmark Dataset for Aerial Image Interpretation: Reviews, Guidances and Million-AIDCode1
DiffMIC: Dual-Guidance Diffusion Network for Medical Image ClassificationCode1
Differentiable Top-k Classification LearningCode1
Diffusion Mechanism in Residual Neural Network: Theory and ApplicationsCode1
DIFFender: Diffusion-Based Adversarial Defense against Patch AttacksCode1
A&B BNN: Add&Bit-Operation-Only Hardware-Friendly Binary Neural NetworkCode1
Confidence-aware multi-modality learning for eye disease screeningCode1
Differentiable Model Compression via Pseudo Quantization NoiseCode1
DISC: Learning From Noisy Labels via Dynamic Instance-Specific Selection and CorrectionCode1
Diversified in-domain synthesis with efficient fine-tuning for few-shot classificationCode1
DGSSC: A Deep Generative Spectral-Spatial Classifier for Imbalanced Hyperspectral ImageryCode1
DEUP: Direct Epistemic Uncertainty PredictionCode1
DGMIL: Distribution Guided Multiple Instance Learning for Whole Slide Image ClassificationCode1
DHP: Differentiable Meta Pruning via HyperNetworksCode1
A Simple Semi-Supervised Learning Framework for Object DetectionCode1
DetectorGuard: Provably Securing Object Detectors against Localized Patch Hiding AttacksCode1
A General Framework For Detecting Anomalous Inputs to DNN ClassifiersCode1
A Simple Interpretable Transformer for Fine-Grained Image Classification and AnalysisCode1
Detecting AutoAttack Perturbations in the Frequency DomainCode1
Diagnose Like a Pathologist: Transformer-Enabled Hierarchical Attention-Guided Multiple Instance Learning for Whole Slide Image ClassificationCode1
Depth-Wise Convolutions in Vision Transformers for Efficient Training on Small DatasetsCode1
Depth Uncertainty in Neural NetworksCode1
Anytime Dense Prediction with Confidence AdaptivityCode1
Designing Network Design SpacesCode1
Dense Contrastive Learning for Self-Supervised Visual Pre-TrainingCode1
A Simple Baseline for Semi-supervised Semantic Segmentation with Strong Data AugmentationCode1
A Single Graph Convolution Is All You Need: Efficient Grayscale Image ClassificationCode1
DIANet: Dense-and-Implicit Attention NetworkCode1
Container: Context Aggregation NetworkCode1
Differentiable Model Scaling using Differentiable TopkCode1
Differentially Private Synthetic Medical Data Generation using Convolutional GANsCode1
Confidence Regularized Self-TrainingCode1
Content-aware Token Sharing for Efficient Semantic Segmentation with Vision TransformersCode1
Diffusion Model as Representation LearnerCode1
Diffusion Visual Counterfactual ExplanationsCode1
Conformer: Local Features Coupling Global Representations for Visual RecognitionCode1
Densely Connected Convolutional NetworksCode1
A Simple Baseline for Low-Budget Active LearningCode1
Direct Differentiable Augmentation SearchCode1
Directional Statistics-based Deep Metric Learning for Image Classification and RetrievalCode1
DISCO: Adversarial Defense with Local Implicit FunctionsCode1
Discretization-Aware Architecture SearchCode1
Discriminator-free Unsupervised Domain Adaptation for Multi-label Image ClassificationCode1
Disentangle and Remerge: Interventional Knowledge Distillation for Few-Shot Object Detection from A Conditional Causal PerspectiveCode1
Disentangling Label Distribution for Long-tailed Visual RecognitionCode1
CondenseNet V2: Sparse Feature Reactivation for Deep NetworksCode1
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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