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 171180 of 10419 papers

TitleStatusHype
TransNeXt: Robust Foveal Visual Perception for Vision TransformersCode2
Adapter is All You Need for Tuning Visual TasksCode2
TransXNet: Learning Both Global and Local Dynamics with a Dual Dynamic Token Mixer for Visual RecognitionCode2
Monarch Mixer: A Simple Sub-Quadratic GEMM-Based ArchitectureCode2
CLIPSelf: Vision Transformer Distills Itself for Open-Vocabulary Dense PredictionCode2
DAT++: Spatially Dynamic Vision Transformer with Deformable AttentionCode2
RevColV2: Exploring Disentangled Representations in Masked Image ModelingCode2
RemoteCLIP: A Vision Language Foundation Model for Remote SensingCode2
MedFMC: A Real-world Dataset and Benchmark For Foundation Model Adaptation in Medical Image ClassificationCode2
NodeFormer: A Scalable Graph Structure Learning Transformer for Node ClassificationCode2
Show:102550
← PrevPage 18 of 1042Next →

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