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 301325 of 10419 papers

TitleStatusHype
GroupMamba: Efficient Group-Based Visual State Space ModelCode2
Adapter is All You Need for Tuning Visual TasksCode2
CLIP-MoE: Towards Building Mixture of Experts for CLIP with Diversified Multiplet UpcyclingCode2
CLIP-Art: Contrastive Pre-training for Fine-Grained Art ClassificationCode2
CLIP-ReID: Exploiting Vision-Language Model for Image Re-Identification without Concrete Text LabelsCode2
A Simple Framework for Contrastive Learning of Visual RepresentationsCode2
Accelerating Transformers with Spectrum-Preserving Token MergingCode2
K-LITE: Learning Transferable Visual Models with External KnowledgeCode2
Context Encoding for Semantic SegmentationCode2
Cross the Gap: Exposing the Intra-modal Misalignment in CLIP via Modality InversionCode2
Big Transfer (BiT): General Visual Representation LearningCode2
A Survey on Mixup Augmentations and BeyondCode2
Learn From Zoom: Decoupled Supervised Contrastive Learning For WCE Image ClassificationCode2
Learning Efficient Convolutional Networks through Network SlimmingCode2
Prompt Pre-Training with Twenty-Thousand Classes for Open-Vocabulary Visual RecognitionCode2
LibFewShot: A Comprehensive Library for Few-shot LearningCode2
Class-Aware Contrastive Semi-Supervised LearningCode1
Class Adaptive Network CalibrationCode1
Class-Aware Patch Embedding Adaptation for Few-Shot Image ClassificationCode1
ACPL: Anti-curriculum Pseudo-labelling for Semi-supervised Medical Image ClassificationCode1
Counterfactual Explanations for Medical Image Classification and Regression using Diffusion AutoencoderCode1
Circumventing Outliers of AutoAugment with Knowledge DistillationCode1
Class-Balanced Active Learning for Image ClassificationCode1
CheXWorld: Exploring Image World Modeling for Radiograph Representation LearningCode1
CheXFusion: Effective Fusion of Multi-View Features using Transformers for Long-Tailed Chest X-Ray ClassificationCode1
Show:102550
← PrevPage 13 of 417Next →

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
5DaViT-HTop 1 Accuracy90.2Unverified
6Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2Unverified
7SwinV2-GTop 1 Accuracy90.17Unverified
8MAWS (ViT-6.5B)Top 1 Accuracy90.1Unverified
9Florence-CoSwin-HTop 1 Accuracy90.05Unverified
10Meta Pseudo Labels (EfficientNet-B6-Wide)Top 1 Accuracy90Unverified