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 4001–4025 of 10420 papers

TitleStatusHype
Long-Tailed Classification of Thorax Diseases on Chest X-Ray: A New Benchmark StudyCode1
An Access Control Method with Secret Key for Semantic Segmentation Models—0
Constraining Pseudo-label in Self-training Unsupervised Domain Adaptation with Energy-based Model—0
Disentangle and Remerge: Interventional Knowledge Distillation for Few-Shot Object Detection from A Conditional Causal PerspectiveCode1
Dense Depth Distillation with Out-of-Distribution Simulated Images—0
Supervised Dimensionality Reduction and Image Classification Utilizing Convolutional AutoencodersCode1
Calibrated Selective ClassificationCode0
TMIC: App Inventor Extension for the Deployment of Image Classification Models Exported from Teachable Machine—0
gSwin: Gated MLP Vision Model with Hierarchical Structure of Shifted Window—0
Radial Basis Function Networks for Convolutional Neural Networks to Learn Similarity Distance Metric and Improve InterpretabilityCode0
Time-lapse image classification using a diffractive neural network—0
Learning from Noisy Labels with Coarse-to-Fine Sample Credibility Modeling—0
Minimizing the Effect of Noise and Limited Dataset Size in Image Classification Using Depth Estimation as an Auxiliary Task with Deep Multitask Learning—0
GCISG: Guided Causal Invariant Learning for Improved Syn-to-real Generalization—0
PLMCL: Partial-Label Momentum Curriculum Learning for Multi-Label Image Classification—0
Image as a Foreign Language: BEiT Pretraining for All Vision and Vision-Language TasksCode0
Multilayer deep feature extraction for visual texture recognition—0
Towards Calibrated Hyper-Sphere Representation via Distribution Overlap Coefficient for Long-tailed LearningCode0
Revisiting ensembling for improving the performance of deep learning models—0
Byzantines can also Learn from History: Fall of Centered Clipping in Federated Learning—0
DiscrimLoss: A Universal Loss for Hard Samples and Incorrect Samples Discrimination—0
Net2Brain: A Toolbox to compare artificial vision models with human brain responsesCode1
Effectiveness of Function Matching in Driving Scene Recognition—0
Exploring Adversarial Robustness of Vision Transformers in the Spectral PerspectiveCode0
Improved Image Classification with Token Fusion—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