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 201225 of 10419 papers

TitleStatusHype
ParC-Net: Position Aware Circular Convolution with Merits from ConvNets and TransformerCode2
Accelerating Transformers with Spectrum-Preserving Token MergingCode2
DEYO: DETR with YOLO for End-to-End Object DetectionCode2
Matryoshka Representation LearningCode2
EdgeNeXt: Efficiently Amalgamated CNN-Transformer Architecture for Mobile Vision ApplicationsCode2
Medical Image Classification with KAN-Integrated Transformers and Dilated Neighborhood AttentionCode2
Deep PCB To COCO ConvertorCode2
Class-Incremental Learning: A SurveyCode2
DaViT: Dual Attention Vision TransformersCode2
DAT++: Spatially Dynamic Vision Transformer with Deformable AttentionCode2
Decoupled Knowledge DistillationCode2
DAMamba: Vision State Space Model with Dynamic Adaptive ScanCode2
DataDream: Few-shot Guided Dataset GenerationCode2
MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision TransformerCode2
CrypTen: Secure Multi-Party Computation Meets Machine LearningCode2
Cross the Gap: Exposing the Intra-modal Misalignment in CLIP via Modality InversionCode2
Current Trends in Deep Learning for Earth Observation: An Open-source Benchmark Arena for Image ClassificationCode2
DenseNets Reloaded: Paradigm Shift Beyond ResNets and ViTsCode2
Effective Data Augmentation With Diffusion ModelsCode2
AutoFormer: Searching Transformers for Visual RecognitionCode2
Contrastive learning of Class-agnostic Activation Map for Weakly Supervised Object Localization and Semantic SegmentationCode2
Multi-Representation Adaptation Network for Cross-domain Image ClassificationCode2
Contrastive Learning Rivals Masked Image Modeling in Fine-tuning via Feature DistillationCode2
Context Encoding for Semantic SegmentationCode2
AEM: Attention Entropy Maximization for Multiple Instance Learning based Whole Slide Image ClassificationCode2
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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