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 4301–4310 of 10420 papers

TitleStatusHype
Uni-Perceiver-MoE: Learning Sparse Generalist Models with Conditional MoEsCode2
Benefits of Overparameterized Convolutional Residual Networks: Function Approximation under Smoothness Constraint—0
Uncovering bias in the PlantVillage datasetCode0
OOD Augmentation May Be at Odds with Open-Set Recognition—0
Learning to generate imaginary tasks for improving generalization in meta-learning—0
Neural Prompt SearchCode2
S3Net: Spectral–Spatial Siamese Network for Few-Shot Hyperspectral Image ClassificationCode1
FixCaps: An Improved Capsules Network for Diagnosis of Skin CancerCode1
Gradient Obfuscation Gives a False Sense of Security in Federated Learning—0
MobileOne: An Improved One millisecond Mobile BackboneCode2
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CoCa (finetuned)Top 1 Accuracy91—Unverified
2Model soups (BASIC-L)Top 1 Accuracy90.98—Unverified
3Model soups (ViT-G/14)Top 1 Accuracy90.94—Unverified
4DaViT-GTop 1 Accuracy90.4—Unverified
5DaViT-HTop 1 Accuracy90.2—Unverified
6Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2—Unverified
7SwinV2-GTop 1 Accuracy90.17—Unverified
8MAWS (ViT-6.5B)Top 1 Accuracy90.1—Unverified
9Florence-CoSwin-HTop 1 Accuracy90.05—Unverified
10Meta Pseudo Labels (EfficientNet-B6-Wide)Top 1 Accuracy90—Unverified