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 11761200 of 10420 papers

TitleStatusHype
Bamboo: Building Mega-Scale Vision Dataset Continually with Human-Machine SynergyCode1
Scalable Penalized Regression for Noise Detection in Learning with Noisy LabelsCode1
Energy-Latency Attacks via Sponge PoisoningCode1
Deep AutoAugmentCode1
Active Token MixerCode1
Deep Multimodal Guidance for Medical Image ClassificationCode1
Self Pre-training with Masked Autoencoders for Medical Image Classification and SegmentationCode1
Graph Attention Transformer Network for Multi-Label Image ClassificationCode1
Selective-Supervised Contrastive Learning with Noisy LabelsCode1
PASS: Part-Aware Self-Supervised Pre-Training for Person Re-IdentificationCode1
Dynamic MLP for Fine-Grained Image Classification by Leveraging Geographical and Temporal InformationCode1
WaveMix: Resource-efficient Token Mixing for ImagesCode1
Class-Aware Contrastive Semi-Supervised LearningCode1
DiT: Self-supervised Pre-training for Document Image TransformerCode1
Random Quantum Neural Networks (RQNN) for Noisy Image RecognitionCode1
Exploring Hierarchical Graph Representation for Large-Scale Zero-Shot Image ClassificationCode1
Evaluating the Adversarial Robustness of Adaptive Test-time DefensesCode1
Attribute Descent: Simulating Object-Centric Datasets on the Content Level and BeyondCode1
Relational Surrogate Loss LearningCode1
TeachAugment: Data Augmentation Optimization Using Teacher KnowledgeCode1
ChimeraMix: Image Classification on Small Datasets via Masked Feature MixingCode1
DataMUX: Data Multiplexing for Neural NetworksCode1
Multi-task UNet: Jointly Boosting Saliency Prediction and Disease Classification on Chest X-ray ImagesCode1
ScoreNet: Learning Non-Uniform Attention and Augmentation for Transformer-Based Histopathological Image ClassificationCode1
Pruning Networks with Cross-Layer Ranking & k-Reciprocal Nearest FiltersCode1
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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