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 1120 of 10419 papers

TitleStatusHype
DINOv2: Learning Robust Visual Features without SupervisionCode6
Patch n' Pack: NaViT, a Vision Transformer for any Aspect Ratio and ResolutionCode6
Sequencer: Deep LSTM for Image ClassificationCode5
Scalable Pre-training of Large Autoregressive Image ModelsCode5
Chinese CLIP: Contrastive Vision-Language Pretraining in ChineseCode5
Multimodal Autoregressive Pre-training of Large Vision EncodersCode5
A ConvNet for the 2020sCode5
Efficient Multimodal Learning from Data-centric PerspectiveCode5
Open-Vocabulary SAM: Segment and Recognize Twenty-thousand Classes InteractivelyCode5
ELEVATER: A Benchmark and Toolkit for Evaluating Language-Augmented Visual ModelsCode4
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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
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