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 126–150 of 10419 papers

TitleStatusHype
Learning Concept-Driven Logical Rules for Interpretable and Generalizable Medical Image ClassificationCode1
Scaling Vision Mamba Across Resolutions via Fractal Traversal—0
Enhancing Transformers Through Conditioned Embedded Tokens—0
AGI-Elo: How Far Are We From Mastering A Task?Code1
Synthetic-Powered Predictive InferenceCode0
EPIC: Explanation of Pretrained Image Classification Networks via PrototypeCode0
Unlabeled Data or Pre-trained Model: Rethinking Semi-Supervised Learning and Pretrain-Finetuning—0
Learning to Adapt to Position Bias in Vision Transformer ClassifiersCode0
An approach based on class activation maps for investigating the effects of data augmentation on neural networks for image classification—0
Expert-Like Reparameterization of Heterogeneous Pyramid Receptive Fields in Efficient CNNs for Fair Medical Image Classification—0
Emergence of Fixational and Saccadic Movements in a Multi-Level Recurrent Attention Model for Vision—0
When majority rules, minority loses: bias amplification of gradient descent—0
A Physics-Inspired Optimizer: Velocity Regularized Adam—0
SRLoRA: Subspace Recomposition in Low-Rank Adaptation via Importance-Based Fusion and Reinitialization—0
Spectral-Spatial Self-Supervised Learning for Few-Shot Hyperspectral Image ClassificationCode1
Denoising Mutual Knowledge Distillation in Bi-Directional Multiple Instance Learning—0
SGD-Mix: Enhancing Domain-Specific Image Classification with Label-Preserving Data Augmentation—0
A Training Framework for Optimal and Stable Training of Polynomial Neural NetworksCode0
Optimal Control for Transformer Architectures: Enhancing Generalization, Robustness and Efficiency—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
CLIP Embeddings for AI-Generated Image Detection: A Few-Shot Study with Lightweight Classifier—0
Marigold: Affordable Adaptation of Diffusion-Based Image Generators for Image AnalysisCode7
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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