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 251275 of 10419 papers

TitleStatusHype
Tencent ML-Images: A Large-Scale Multi-Label Image Database for Visual Representation LearningCode2
Test-Time Prompt Tuning for Zero-Shot Generalization in Vision-Language ModelsCode2
The Equalization Losses: Gradient-Driven Training for Long-tailed Object RecognitionCode2
TinyViM: Frequency Decoupling for Tiny Hybrid Vision MambaCode2
ParC-Net: Position Aware Circular Convolution with Merits from ConvNets and TransformerCode2
DEYO: DETR with YOLO for End-to-End Object DetectionCode2
DenseNets Reloaded: Paradigm Shift Beyond ResNets and ViTsCode2
Decoupled Knowledge DistillationCode2
Deep PCB To COCO ConvertorCode2
DGR-MIL: Exploring Diverse Global Representation in Multiple Instance Learning for Whole Slide Image ClassificationCode2
EdgeNeXt: Efficiently Amalgamated CNN-Transformer Architecture for Mobile Vision ApplicationsCode2
DataDream: Few-shot Guided Dataset GenerationCode2
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
ConvMAE: Masked Convolution Meets Masked AutoencodersCode2
Contrastive Learning Rivals Masked Image Modeling in Fine-tuning via Feature DistillationCode2
CroCo: Self-Supervised Pre-training for 3D Vision Tasks by Cross-View CompletionCode2
Continual Forgetting for Pre-trained Vision ModelsCode2
DAMamba: Vision State Space Model with Dynamic Adaptive ScanCode2
Context Encoding for Semantic SegmentationCode2
Class-Incremental Learning: A SurveyCode2
Contrastive learning of Class-agnostic Activation Map for Weakly Supervised Object Localization and Semantic SegmentationCode2
CrossFormer++: A Versatile Vision Transformer Hinging on Cross-scale AttentionCode2
DAT++: Spatially Dynamic Vision Transformer with Deformable AttentionCode2
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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