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 2351–2400 of 10419 papers

TitleStatusHype
MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images—0
COLORA: Efficient Fine-Tuning for Convolutional Models with a Study Case on Optical Coherence Tomography Image Classification—0
Feature Preserving Shrinkage on Bayesian Neural Networks via the R2D2 Prior—0
Ownership Verification of DNN Models Using White-Box Adversarial Attacks with Specified Probability Manipulation—0
SemSegBench & DetecBench: Benchmarking Reliability and Generalization Beyond ClassificationCode0
EVM-Fusion: An Explainable Vision Mamba Architecture with Neural Algorithmic Fusion—0
TULiP: Test-time Uncertainty Estimation via Linearization and Weight Perturbation—0
When VLMs Meet Image Classification: Test Sets Renovation via Missing Label Identification—0
Accelerating Targeted Hard-Label Adversarial Attacks in Low-Query Black-Box SettingsCode0
Fusion of Foundation and Vision Transformer Model Features for Dermatoscopic Image Classification—0
Swin Transformer for Robust CGI Images Detection: Intra- and Inter-Dataset Analysis across Multiple Color Spaces—0
Parameter-Efficient Fine-Tuning of Multispectral Foundation Models for Hyperspectral Image Classification—0
Domain Adaptive Skin Lesion Classification via Conformal Ensemble of Vision Transformers—0
SNAP: A Benchmark for Testing the Effects of Capture Conditions on Fundamental Vision TasksCode0
Beyond Linearity: Squeeze-and-Recalibrate Blocks for Few-Shot Whole Slide Image Classification—0
Adaptive Temperature Scaling with Conformal Prediction—0
FragFake: A Dataset for Fine-Grained Detection of Edited Images with Vision Language ModelsCode0
Aligning Explanations with Human CommunicationCode0
GradPCA: Leveraging NTK Alignment for Reliable Out-of-Distribution Detection—0
Scaling Vision Mamba Across Resolutions via Fractal Traversal—0
Intra-class Patch Swap for Self-DistillationCode0
Large Language Models Implicitly Learn to See and Hear Just By Reading—0
KO: Kinetics-inspired Neural Optimizer with PDE Simulation Approaches—0
Synthetic-Powered Predictive InferenceCode0
When majority rules, minority loses: bias amplification of gradient descent—0
A Physics-Inspired Optimizer: Velocity Regularized Adam—0
Enhancing Transformers Through Conditioned Embedded Tokens—0
Unlabeled Data or Pre-trained Model: Rethinking Semi-Supervised Learning and Pretrain-Finetuning—0
An approach based on class activation maps for investigating the effects of data augmentation on neural networks for image classification—0
EPIC: Explanation of Pretrained Image Classification Networks via PrototypeCode0
Emergence of Fixational and Saccadic Movements in a Multi-Level Recurrent Attention Model for Vision—0
Expert-Like Reparameterization of Heterogeneous Pyramid Receptive Fields in Efficient CNNs for Fair Medical Image Classification—0
Learning to Adapt to Position Bias in Vision Transformer ClassifiersCode0
SRLoRA: Subspace Recomposition in Low-Rank Adaptation via Importance-Based Fusion and Reinitialization—0
SGD-Mix: Enhancing Domain-Specific Image Classification with Label-Preserving Data Augmentation—0
Denoising Mutual Knowledge Distillation in Bi-Directional Multiple Instance Learning—0
Humble your Overconfident Networks: Unlearning Overfitting via Sequential Monte Carlo Tempered Deep Ensembles—0
CheX-DS: Improving Chest X-ray Image Classification with Ensemble Learning Based on DenseNet and Swin Transformer—0
Privacy-Aware Lifelong LearningCode0
MCU: Improving Machine Unlearning through Mode Connectivity—0
A Training Framework for Optimal and Stable Training of Polynomial Neural NetworksCode0
Optimal Control for Transformer Architectures: Enhancing Generalization, Robustness and Efficiency—0
CLIP Embeddings for AI-Generated Image Detection: A Few-Shot Study with Lightweight Classifier—0
Quantum-Enhanced Parameter-Efficient Learning for Typhoon Trajectory Forecasting—0
CNN and ViT Efficiency Study on Tiny ImageNet and DermaMNIST Datasets—0
MoKD: Multi-Task Optimization for Knowledge Distillation—0
Convolutional Spiking Neural Network for Image Classification—0
Empowering Vision Transformers with Multi-Scale Causal Intervention for Long-Tailed Image Classification—0
Synthetic Similarity Search in Automotive Production—0
Discovering Fine-Grained Visual-Concept Relations by Disentangled Optimal Transport Concept Bottleneck Models—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