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 30013025 of 10420 papers

TitleStatusHype
Time Traveling to Defend Against Adversarial Example Attacks in Image Classification0
More Experts Than Galaxies: Conditionally-overlapping Experts With Biologically-Inspired Fixed RoutingCode0
When the Small-Loss Trick is Not Enough: Multi-Label Image Classification with Noisy Labels Applied to CCTV Sewer Inspections0
What is Left After Distillation? How Knowledge Transfer Impacts Fairness and Bias0
Frequency-Temporal Attention Network for Remote Sensing Imagery Change DetectionCode0
CSA: Data-efficient Mapping of Unimodal Features to Multimodal Features0
Explainability of Deep Neural Networks for Brain Tumor DetectionCode0
JPEG Inspired Deep LearningCode0
Optimizing Estimators of Squared Calibration Errors in Classification0
Convex Distillation: Efficient Compression of Deep Networks via Convex Optimization0
A second-order-like optimizer with adaptive gradient scaling for deep learningCode0
Stochastic Kernel Regularisation Improves Generalisation in Deep Kernel MachinesCode0
Core Tokensets for Data-efficient Sequential Training of TransformersCode0
Contrastive Learning to Fine-Tune Feature Extraction Models for the Visual Cortex0
Conformal Structured PredictionCode0
Art Forgery Detection using Kolmogorov Arnold and Convolutional Neural Networks0
LoTLIP: Improving Language-Image Pre-training for Long Text Understanding0
IGroupSS-Mamba: Interval Group Spatial-Spectral Mamba for Hyperspectral Image Classification0
Variable Resolution Pixel Quantization for Low Power Machine Vision Application on Edge0
Control-oriented Clustering of Visual Latent Representation0
MECFormer: Multi-task Whole Slide Image Classification with Expert Consultation Network0
Interpret Your Decision: Logical Reasoning Regularization for Generalization in Visual ClassificationCode0
IT^3: Idempotent Test-Time Training0
Impact of Regularization on Calibration and Robustness: from the Representation Space Perspective0
Classification-Denoising Networks0
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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
5DaViT-HTop 1 Accuracy90.2Unverified
6Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2Unverified
7SwinV2-GTop 1 Accuracy90.17Unverified
8MAWS (ViT-6.5B)Top 1 Accuracy90.1Unverified
9Florence-CoSwin-HTop 1 Accuracy90.05Unverified
10Meta Pseudo Labels (EfficientNet-B6-Wide)Top 1 Accuracy90Unverified