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 6151–6200 of 10420 papers

TitleStatusHype
Exploiting Invariance in Training Deep Neural NetworksCode0
DAP: Detection-Aware Pre-training with Weak SupervisionCode0
MT3: Meta Test-Time Training for Self-Supervised Test-Time AdaptionCode1
Distribution Alignment: A Unified Framework for Long-tail Visual RecognitionCode1
Model-Contrastive Federated LearningCode1
Learning Representational Invariances for Data-Efficient Action RecognitionCode1
Rethinking Spatial Dimensions of Vision TransformersCode1
Automating Defense Against Adversarial Attacks: Discovery of Vulnerabilities and Application of Multi-INT Imagery to Protect Deployed Models—0
Data Augmentation in a Hybrid Approach for Aspect-Based Sentiment AnalysisCode0
"Weak AI" is Likely to Never Become "Strong AI", So What is its Greatest Value for us?—0
Selective Output Smoothing Regularization: Regularize Neural Networks by Softening Output Distributions—0
Rethinking Neural Operations for Diverse TasksCode1
Classifying Video based on Automatic Content Detection Overview—0
ViViT: A Video Vision TransformerCode1
Capsule Network is Not More Robust than Convolutional Network—0
Multi-Scale Vision Longformer: A New Vision Transformer for High-Resolution Image EncodingCode1
CvT: Introducing Convolutions to Vision TransformersCode1
[Re] Rigging the Lottery: Making All Tickets WinnersCode1
Explaining Representation by Mutual Information—0
BA^2M: A Batch Aware Attention Module for Image Classification—0
TransCenter: Transformers with Dense Representations for Multiple-Object TrackingCode1
IoU Attack: Towards Temporally Coherent Black-Box Adversarial Attack for Visual Object TrackingCode1
On the benefits of robust models in modulation recognition—0
Going Deeper Into Face Detection: A Survey—0
CrossViT: Cross-Attention Multi-Scale Vision Transformer for Image ClassificationCode1
Explore the Knowledge contained in Network Weights to Obtain Sparse Neural Networks—0
Understanding Robustness of Transformers for Image Classification—0
Distilling Object Detectors via Decoupled FeaturesCode1
MedSelect: Selective Labeling for Medical Image Classification Combining Meta-Learning with Deep Reinforcement LearningCode1
Contrastive Learning based Hybrid Networks for Long-Tailed Image Classification—0
Unsupervised Robust Domain Adaptation without Source Data—0
A Comprehensive Review of Image Analysis Methods for Microorganism Counting: From Classical Image Processing to Deep Learning Approaches—0
ECINN: Efficient Counterfactuals from Invertible Neural NetworksCode0
Swin Transformer: Hierarchical Vision Transformer using Shifted WindowsCode2
Spatial-spectral Hyperspectral Image Classification via Multiple Random Anchor Graphs Ensemble Learning—0
Preserve, Promote, or Attack? GNN Explanation via Topology Perturbation—0
Self-Supervised Training Enhances Online Continual Learning—0
Contrast to Divide: Self-Supervised Pre-Training for Learning with Noisy LabelsCode1
Diverse Branch Block: Building a Convolution as an Inception-like UnitCode1
Factors of Influence for Transfer Learning across Diverse Appearance Domains and Task Types—0
W2WNet: a two-module probabilistic Convolutional Neural Network with embedded data cleansing functionality—0
AutoMix: Unveiling the Power of Mixup for Stronger ClassifiersCode1
EPRNet: Efficient Pyramid Representation Network for Real-Time Street Scene SegmentationCode0
Enhanced Gradient for Differentiable Architecture Search—0
BossNAS: Exploring Hybrid CNN-transformers with Block-wisely Self-supervised Neural Architecture SearchCode1
MetaSAug: Meta Semantic Augmentation for Long-Tailed Visual RecognitionCode1
Scaling Local Self-Attention for Parameter Efficient Visual BackbonesCode1
Characterizing and Improving the Robustness of Self-Supervised Learning through Background Augmentations—0
DeepViT: Towards Deeper Vision TransformerCode1
Deep Neural Networks Learn Meta-Structures from Noisy Labels in Semantic Segmentation—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
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