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 4326–4350 of 10420 papers

TitleStatusHype
Protect Federated Learning Against Backdoor Attacks via Data-Free Trigger Generation—0
Knowledge-Aware Prompt Tuning for Generalizable Vision-Language Models—0
Food Image Classification and Segmentation with Attention-based Multiple Instance Learning—0
Seeing the Intangible: Survey of Image Classification into High-Level and Abstract Categories—0
LDCSF: Local depth convolution-based Swim framework for classifying multi-label histopathology imagesCode0
Measuring the Effect of Causal Disentanglement on the Adversarial Robustness of Neural Network Models—0
Foundation Model-oriented Robustness: Robust Image Model Evaluation with Pretrained Models—0
CoNe: Contrast Your Neighbours for Supervised Image ClassificationCode0
Quantile-based Maximum Likelihood Training for Outlier DetectionCode0
Partition-and-Debias: Agnostic Biases Mitigation via A Mixture of Biases-Specific ExpertsCode0
ASPIRE: Language-Guided Data Augmentation for Improving Robustness Against Spurious CorrelationsCode0
The Impact of Background Removal on Performance of Neural Networks for Fashion Image Classification and Segmentation—0
Latent State Models of Training DynamicsCode0
Learning Through Guidance: Knowledge Distillation for Endoscopic Image Classification—0
ResBuilder: Automated Learning of Depth with Residual Structures—0
How To Overcome Confirmation Bias in Semi-Supervised Image Classification By Active Learning—0
Multi-Receiver Task-Oriented Communications via Multi-Task Deep Learning—0
Unified Data-Free Compression: Pruning and Quantization without Fine-Tuning—0
Distance Matters For Improving Performance Estimation Under Covariate ShiftCode0
Robustness Stress Testing in Medical Image ClassificationCode0
Contrastive Bi-Projector for Unsupervised Domain AdaptionCode0
Neural Networks at a Fraction with Pruned Quaternions—0
TorchQL: A Programming Framework for Integrity Constraints in Machine Learning—0
Free-ATM: Exploring Unsupervised Learning on Diffusion-Generated Images with Free Attention Masks—0
Distributionally Robust Optimization and Invariant Representation Learning for Addressing Subgroup Underrepresentation: Mechanisms and Limitations—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