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 13511375 of 10419 papers

TitleStatusHype
Saliency-guided and Patch-based Mixup for Long-tailed Skin Cancer Image Classification0
Fine-grained Classes and How to Find ThemCode1
Robust Image Classification in the Presence of Out-of-Distribution and Adversarial Samples Using Attractors in Neural Networks0
AI-Based Copyright Detection Of An Image In a Video Using Degree Of Similarity And Image Hashing0
Adaptive Randomized Smoothing: Certified Adversarial Robustness for Multi-Step DefencesCode0
LieRE: Generalizing Rotary Position EncodingsCode1
Comparison of fine-tuning strategies for transfer learning in medical image classification0
Forgetting Order of Continual Learning: Examples That are Learned First are Forgotten Last0
How Out-of-Distribution Detection Learning Theory Enhances Transformer: Learnability and Reliability0
LaCoOT: Layer Collapse through Optimal Transport0
MirrorCheck: Efficient Adversarial Defense for Vision-Language Models0
The Penalized Inverse Probability Measure for Conformal Classification0
Large-Scale Evaluation of Open-Set Image Classification TechniquesCode0
Conceptual Learning via Embedding Approximations for Reinforcing Interpretability and TransparencyCode0
DenoiseRep: Denoising Model for Representation LearningCode1
A^2-MAE: A spatial-temporal-spectral unified remote sensing pre-training method based on anchor-aware masked autoencoder0
Transformation-Dependent Adversarial Attacks0
Multi-Teacher Multi-Objective Meta-Learning for Zero-Shot Hyperspectral Band Selection0
AdaNCA: Neural Cellular Automata As Adaptors For More Robust Vision Transformer0
Intelligent Multi-View Test Time AugmentationCode0
DistilDoc: Knowledge Distillation for Visually-Rich Document Applications0
Small Scale Data-Free Knowledge DistillationCode1
Unveiling the Power of Wavelets: A Wavelet-based Kolmogorov-Arnold Network for Hyperspectral Image ClassificationCode2
Accurate Explanation Model for Image Classifiers using Class Association EmbeddingCode0
DualMamba: A Lightweight Spectral-Spatial Mamba-Convolution Network for Hyperspectral Image Classification0
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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
5Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2Unverified
6DaViT-HTop 1 Accuracy90.2Unverified
7SwinV2-GTop 1 Accuracy90.17Unverified
8MAWS (ViT-6.5B)Top 1 Accuracy90.1Unverified
9Florence-CoSwin-HTop 1 Accuracy90.05Unverified
10RevCol-HTop 1 Accuracy90Unverified