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 3226–3250 of 10420 papers

TitleStatusHype
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