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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 6251–6275 of 10420 papers

TitleStatusHype
Spatially Consistent Representation LearningCode1
TransMed: Transformers Advance Multi-modal Medical Image Classification—0
Involution: Inverting the Inherence of Convolution for Visual RecognitionCode2
MixMo: Mixing Multiple Inputs for Multiple Outputs via Deep SubnetworksCode1
Cut-Thumbnail: A Novel Data Augmentation for Convolutional Neural NetworkCode0
Split Computing and Early Exiting for Deep Learning Applications: Survey and Research ChallengesCode1
Multimodal Representation Learning via Maximization of Local Mutual InformationCode1
Improving Global Adversarial Robustness Generalization With Adversarially Trained GAN—0
TransBTS: Multimodal Brain Tumor Segmentation Using TransformerCode1
Efficient Model Performance Estimation via Feature Histories—0
Spectral Tensor Train Parameterization of Deep Learning LayersCode1
Student-Teacher Feature Pyramid Matching for Anomaly DetectionCode1
A Retrospective Approximation Approach for Smooth Stochastic Optimization—0
End-to-end optimized image compression for multiple machine tasks—0
LongReMix: Robust Learning with High Confidence Samples in a Noisy Label EnvironmentCode0
Selective Replay Enhances Learning in Online Continual Analogical ReasoningCode0
Contextual Dropout: An Efficient Sample-Dependent Dropout ModuleCode0
Unified Robust Training for Graph NeuralNetworks against Label Noise—0
VIPriors 1: Visual Inductive Priors for Data-Efficient Deep Learning ChallengesCode1
Don't Forget to Sign the Gradients!Code0
Measuring Model Biases in the Absence of Ground Truth—0
SCRIB: Set-classifier with Class-specific Risk Bounds for Blackbox Models—0
Redundant Information Neural Estimation—0
Hard-label Manifolds: Unexpected Advantages of Query Efficiency for Finding On-manifold Adversarial Examples—0
QAIR: Practical Query-efficient Black-Box Attacks for Image Retrieval—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
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