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 22012225 of 10420 papers

TitleStatusHype
Feature Extraction for Hyperspectral Imagery: The Evolution from Shallow to Deep (Overview and Toolbox)Code1
Contrastive Masked Autoencoders are Stronger Vision LearnersCode1
A survey on attention mechanisms for medical applications: are we moving towards better algorithms?Code1
Feature Re-calibration based Multiple Instance Learning for Whole Slide Image ClassificationCode1
Contrast to Divide: Self-Supervised Pre-Training for Learning with Noisy LabelsCode1
FedCV: A Federated Learning Framework for Diverse Computer Vision TasksCode1
DEUP: Direct Epistemic Uncertainty PredictionCode1
Controllable Orthogonalization in Training DNNsCode1
FedMLP: Federated Multi-Label Medical Image Classification under Task HeterogeneityCode1
FedProc: Prototypical Contrastive Federated Learning on Non-IID dataCode1
A Bregman Learning Framework for Sparse Neural NetworksCode1
FedSOL: Stabilized Orthogonal Learning with Proximal Restrictions in Federated LearningCode1
FewSAR: A Few-shot SAR Image Classification BenchmarkCode1
Few-Shot Image Classification Benchmarks are Too Far From Reality: Build Back Better with Semantic Task SamplingCode1
FewVS: A Vision-Semantics Integration Framework for Few-Shot Image ClassificationCode1
FFT-based Dynamic Token Mixer for VisionCode1
CrAM: A Compression-Aware MinimizerCode1
Fibottention: Inceptive Visual Representation Learning with Diverse Attention Across HeadsCode1
DetectorGuard: Provably Securing Object Detectors against Localized Patch Hiding AttacksCode1
ConvMLP: Hierarchical Convolutional MLPs for VisionCode1
A Survey on Transferability of Adversarial Examples across Deep Neural NetworksCode1
Fine-grained Classes and How to Find ThemCode1
DGMIL: Distribution Guided Multiple Instance Learning for Whole Slide Image ClassificationCode1
Cross-Domain Ensemble Distillation for Domain GeneralizationCode1
DIANet: Dense-and-Implicit Attention NetworkCode1
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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