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 24412450 of 10420 papers

TitleStatusHype
LCReg: Long-Tailed Image Classification with Latent Categories based Recognition0
OLID I: an open leaf image dataset for plant stress recognition0
Language Models as Black-Box Optimizers for Vision-Language ModelsCode1
Padding-free Convolution based on Preservation of Differential Characteristics of Kernels0
Accelerating Deep Neural Networks via Semi-Structured Activation Sparsity0
Strong-Weak Integrated Semi-supervision for Unsupervised Single and Multi Target Domain Adaptation0
Computer Vision Pipeline for Automated Antarctic Krill Analysis0
GlobalDoc: A Cross-Modal Vision-Language Framework for Real-World Document Image Retrieval and Classification0
Divergences in Color Perception between Deep Neural Networks and HumansCode1
SparseSwin: Swin Transformer with Sparse Transformer BlockCode1
Show:102550
← PrevPage 245 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
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