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

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Showing 851–900 of 10419 papers

TitleStatusHype
What is Left After Distillation? How Knowledge Transfer Impacts Fairness and Bias—0
Time Traveling to Defend Against Adversarial Example Attacks in Image Classification—0
When the Small-Loss Trick is Not Enough: Multi-Label Image Classification with Noisy Labels Applied to CCTV Sewer Inspections—0
Explainability of Deep Neural Networks for Brain Tumor DetectionCode0
CSA: Data-efficient Mapping of Unimodal Features to Multimodal Features—0
More Experts Than Galaxies: Conditionally-overlapping Experts With Biologically-Inspired Fixed RoutingCode0
JPEG Inspired Deep LearningCode0
QuadMamba: Learning Quadtree-based Selective Scan for Visual State Space ModelCode1
Optimizing Estimators of Squared Calibration Errors in Classification—0
Convex Distillation: Efficient Compression of Deep Networks via Convex Optimization—0
Parameter Efficient Fine-tuning via Explained Variance AdaptationCode1
FACMIC: Federated Adaptative CLIP Model for Medical Image ClassificationCode1
NegMerge: Consensual Weight Negation for Strong Machine UnlearningCode1
A second-order-like optimizer with adaptive gradient scaling for deep learningCode0
Stochastic Kernel Regularisation Improves Generalisation in Deep Kernel MachinesCode0
Contrastive Learning to Fine-Tune Feature Extraction Models for the Visual Cortex—0
Core Tokensets for Data-efficient Sequential Training of TransformersCode0
Conformal Structured PredictionCode0
Variable Resolution Pixel Quantization for Low Power Machine Vision Application on Edge—0
SELECT: A Large-Scale Benchmark of Data Curation Strategies for Image ClassificationCode1
IGroupSS-Mamba: Interval Group Spatial-Spectral Mamba for Hyperspectral Image Classification—0
LoTLIP: Improving Language-Image Pre-training for Long Text Understanding—0
Art Forgery Detection using Kolmogorov Arnold and Convolutional Neural Networks—0
Control-oriented Clustering of Visual Latent Representation—0
Interpret Your Decision: Logical Reasoning Regularization for Generalization in Visual ClassificationCode0
MECFormer: Multi-task Whole Slide Image Classification with Expert Consultation Network—0
Impact of Regularization on Calibration and Robustness: from the Representation Space Perspective—0
IT^3: Idempotent Test-Time Training—0
A Retention-Centric Framework for Continual Learning with Guaranteed Model Developmental SafetyCode0
Classification-Denoising Networks—0
Selective Transformer for Hyperspectral Image Classification—0
Rethinking VLMs and LLMs for Image Classification—0
On Expert Estimation in Hierarchical Mixture of Experts: Beyond Softmax Gating Functions—0
Lie Algebra Canonicalization: Equivariant Neural Operators under arbitrary Lie Groups—0
LoGra-Med: Long Context Multi-Graph Alignment for Medical Vision-Language Model—0
Hard Negative Sample Mining for Whole Slide Image ClassificationCode0
CTARR: A fast and robust method for identifying anatomical regions on CT images via atlas registrationCode0
BiSSL: Enhancing the Alignment Between Self-Supervised Pretraining and Downstream Fine-Tuning via Bilevel Optimization—0
SynCo: Synthetic Hard Negatives in Contrastive Learning for Better Unsupervised Visual RepresentationsCode0
Personalized Quantum Federated Learning for Privacy Image Classification—0
MONICA: Benchmarking on Long-tailed Medical Image ClassificationCode1
Kolmogorov-Arnold Network AutoencodersCode0
Local-to-Global Self-Supervised Representation Learning for Diabetic Retinopathy Grading—0
Deep Nets with Subsampling Layers Unwittingly Discard Useful Activations at Test-TimeCode0
NECOMIMI: Neural-Cognitive Multimodal EEG-informed Image Generation with Diffusion ModelsCode0
KPCA-CAM: Visual Explainability of Deep Computer Vision Models using Kernel PCACode0
Classroom-Inspired Multi-Mentor Distillation with Adaptive Learning Strategies—0
Satellite image classification with neural quantum kernels—0
Fine-Tuning Personalization in Federated Learning to Mitigate Adversarial Clients—0
SATA: Spatial Autocorrelation Token Analysis for Enhancing the Robustness of Vision TransformersCode0
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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