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 151–175 of 10419 papers

TitleStatusHype
Quantum-Enhanced Parameter-Efficient Learning for Typhoon Trajectory Forecasting—0
CNN and ViT Efficiency Study on Tiny ImageNet and DermaMNIST Datasets—0
Empowering Vision Transformers with Multi-Scale Causal Intervention for Long-Tailed Image Classification—0
Convolutional Spiking Neural Network for Image Classification—0
MoKD: Multi-Task Optimization for Knowledge Distillation—0
Discovering Fine-Grained Visual-Concept Relations by Disentangled Optimal Transport Concept Bottleneck Models—0
Hierarchical Sparse Attention Framework for Computationally Efficient Classification of Biological Cells—0
Synthetic Similarity Search in Automotive Production—0
Matrix Is All You Need—0
Active Learning for Multi-class Image Classification—0
Image Classification Using a Diffusion Model as a Pre-Training Model—0
A Vision-Language Foundation Model for Leaf Disease IdentificationCode0
NeuRN: Neuro-inspired Domain Generalization for Image Classification—0
Improving Generalizability of Kolmogorov-Arnold Networks via Error-Correcting Output CodesCode0
Adapting a Segmentation Foundation Model for Medical Image Classification—0
Achieving 3D Attention via Triplet Squeeze and Excitation Block—0
Efficient Quantum Convolutional Neural Networks for Image Classification: Overcoming Hardware Constraints—0
In-Context Learning for Label-Efficient Cancer Image Classification in Oncology—0
V-EfficientNets: Vector-Valued Efficiently Scaled Convolutional Neural Network ModelsCode0
Hide & Seek: Transformer Symmetries Obscure Sharpness & Riemannian Geometry Finds It—0
Biomed-DPT: Dual Modality Prompt Tuning for Biomedical Vision-Language ModelsCode0
Direct Image Classification from Fourier Ptychographic Microscopy Measurements without Reconstruction—0
Threshold Modulation for Online Test-Time Adaptation of Spiking Neural NetworksCode0
ORXE: Orchestrating Experts for Dynamically Configurable Efficiency—0
FRAIN to Train: A Fast-and-Reliable Solution for Decentralized Federated LearningCode0
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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