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

Showing 9511000 of 10419 papers

TitleStatusHype
Learnable Polyphase Sampling for Shift Invariant and Equivariant Convolutional NetworksCode1
SageMix: Saliency-Guided Mixup for Point CloudsCode1
WaveMix-Lite: A Resource-efficient Neural Network for Image AnalysisCode1
ERNIE-Layout: Layout Knowledge Enhanced Pre-training for Visually-rich Document UnderstandingCode1
Latency-aware Spatial-wise Dynamic NetworksCode1
Multi-Granularity Cross-modal Alignment for Generalized Medical Visual Representation LearningCode1
Token-Label Alignment for Vision TransformersCode1
STSC-SNN: Spatio-Temporal Synaptic Connection with Temporal Convolution and Attention for Spiking Neural NetworksCode1
OPERA: Omni-Supervised Representation Learning with Hierarchical SupervisionsCode1
Understanding the Failure of Batch Normalization for Transformers in NLPCode1
Unsupervised RGB-to-Thermal Domain Adaptation via Multi-Domain Attention NetworkCode1
Online Training Through Time for Spiking Neural NetworksCode1
Bi-directional Weakly Supervised Knowledge Distillation for Whole Slide Image ClassificationCode1
SVL-Adapter: Self-Supervised Adapter for Vision-Language Pretrained ModelsCode1
Robustness Certification of Visual Perception Models via Camera Motion SmoothingCode1
MOAT: Alternating Mobile Convolution and Attention Brings Strong Vision ModelsCode1
Expediting Large-Scale Vision Transformer for Dense Prediction without Fine-tuningCode1
LPT: Long-tailed Prompt Tuning for Image ClassificationCode1
Towards a Unified View on Visual Parameter-Efficient Transfer LearningCode1
OCD: Learning to Overfit with Conditional Diffusion ModelsCode1
Two-Stream Transformer for Multi-Label Image ClassificationCode1
Learning Hierarchical Image Segmentation For Recognition and By RecognitionCode1
Semi-Supervised Single-View 3D Reconstruction via Prototype Shape PriorsCode1
An In-depth Study of Stochastic BackpropagationCode1
TAD: A Large-Scale Benchmark for Traffic Accidents Detection from Video SurveillanceCode1
Capsule Network based Contrastive Learning of Unsupervised Visual RepresentationsCode1
Dynamic Graph Message Passing Networks for Visual RecognitionCode1
CoV-TI-Net: Transferred Initialization with Modified End Layer for COVID-19 DiagnosisCode1
Visual Recognition with Deep Nearest CentroidsCode1
Combining Metric Learning and Attention Heads For Accurate and Efficient Multilabel Image ClassificationCode1
PSAQ-ViT V2: Towards Accurate and General Data-Free Quantization for Vision TransformersCode1
DeepNoise: Signal and Noise Disentanglement based on Classifying Fluorescent Microscopy Images via Deep LearningCode1
Communication-Efficient and Privacy-Preserving Feature-based Federated Transfer LearningCode1
DUET: A Tuning-Free Device-Cloud Collaborative Parameters Generation Framework for Efficient Device Model GeneralizationCode1
Data Feedback Loops: Model-driven Amplification of Dataset BiasesCode1
An Enhanced Scheme for Reducing the Complexity of Pointwise Convolutions in CNNs for Image Classification Based on Interleaved Grouped Filters without Divisibility ConstraintsCode1
Instance-Dependent Noisy Label Learning via Graphical ModellingCode1
SAFE: Sensitivity-Aware Features for Out-of-Distribution Object DetectionCode1
Long-Tailed Classification of Thorax Diseases on Chest X-Ray: A New Benchmark StudyCode1
Disentangle and Remerge: Interventional Knowledge Distillation for Few-Shot Object Detection from A Conditional Causal PerspectiveCode1
Supervised Dimensionality Reduction and Image Classification Utilizing Convolutional AutoencodersCode1
Net2Brain: A Toolbox to compare artificial vision models with human brain responsesCode1
Your ViT is Secretly a Hybrid Discriminative-Generative Diffusion ModelCode1
Shuffle Instances-based Vision Transformer for Pancreatic Cancer ROSE Image ClassificationCode1
MixSKD: Self-Knowledge Distillation from Mixup for Image RecognitionCode1
Patching open-vocabulary models by interpolating weightsCode1
PatchDropout: Economizing Vision Transformers Using Patch DropoutCode1
Almost-Orthogonal Layers for Efficient General-Purpose Lipschitz NetworksCode1
Semi-Supervised Hyperspectral Image Classification Using a Probabilistic Pseudo-Label Generation FrameworkCode1
Semantic Interleaving Global Channel Attention for Multilabel Remote Sensing Image ClassificationCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CoCa (finetuned)Top 1 Accuracy91Unverified
2Model soups (BASIC-L)Top 1 Accuracy90.98Unverified
3Model soups (ViT-G/14)Top 1 Accuracy90.94Unverified
4DaViT-GTop 1 Accuracy90.4Unverified
5Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2Unverified
6DaViT-HTop 1 Accuracy90.2Unverified
7SwinV2-GTop 1 Accuracy90.17Unverified
8MAWS (ViT-6.5B)Top 1 Accuracy90.1Unverified
9Florence-CoSwin-HTop 1 Accuracy90.05Unverified
10RevCol-HTop 1 Accuracy90Unverified