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 3351–3375 of 10420 papers

TitleStatusHype
FV-MgNet: Fully Connected V-cycle MgNet for Interpretable Time Series Forecasting—0
Image-Based Vehicle Classification by Synergizing Features from Supervised and Self-Supervised Learning Paradigms—0
Deep Dependency Networks for Multi-Label Classification—0
Weight Prediction Boosts the Convergence of AdamW—0
Structured mutation inspired by evolutionary theory enriches population performance and diversity—0
mPLUG-2: A Modularized Multi-modal Foundation Model Across Text, Image and VideoCode4
NASiam: Efficient Representation Learning using Neural Architecture Search for Siamese NetworksCode0
Does Deep Active Learning Work in the Wild?—0
Training with Mixed-Precision Floating-Point Assignments—0
UPop: Unified and Progressive Pruning for Compressing Vision-Language TransformersCode1
Inference Time Evidences of Adversarial Attacks for Forensic on Transformers—0
Reverse engineering adversarial attacks with fingerprints from adversarial examples—0
Rethinking Soft Label in Label Distribution Learning Perspective—0
Transfer Learning and Class Decomposition for Detecting the Cognitive Decline of Alzheimer Disease—0
NP-Match: Towards a New Probabilistic Model for Semi-Supervised LearningCode1
Massively Scaling Heteroscedastic Classifiers—0
Lateralized Learning for Multi-Class Visual Classification Tasks—0
DAFD: Domain Adaptation via Feature Disentanglement for Image Classification—0
Equivariant Differentially Private Deep Learning: Why DP-SGD Needs Sparser ModelsCode0
NeSyFOLD: Neurosymbolic Framework for Interpretable Image ClassificationCode0
Identifying Adversarially Attackable and Robust SamplesCode0
Language-Driven Anchors for Zero-Shot Adversarial RobustnessCode0
SeaFormer++: Squeeze-enhanced Axial Transformer for Mobile Visual RecognitionCode2
The Influences of Color and Shape Features in Visual Contrastive Learning—0
PhaVIP: Phage VIrion Protein classification based on chaos game representation and Vision TransformerCode1
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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