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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 4401–4425 of 10420 papers

TitleStatusHype
Boosting Multi-Label Image Classification with Complementary Parallel Self-DistillationCode1
Deep Image Retrieval is not Robust to Label Noise—0
CNNs Avoid Curse of Dimensionality by Learning on Patches—0
Learning Muti-expert Distribution Calibration for Long-tailed Video Classification—0
Recent Advances in Embedding Methods for Multi-Object Tracking: A Survey—0
muNet: Evolving Pretrained Deep Neural Networks into Scalable Auto-tuning Multitask Systems—0
Facing the Void: Overcoming Missing Data in Multi-View ImageryCode0
Vision Transformers in 2022: An Update on Tiny ImageNetCode1
Knowledge Distillation from A Stronger TeacherCode1
A Study on Transformer Configuration and Training Objective—0
PSO-Convolutional Neural Networks with Heterogeneous Learning RateCode0
Towards Better Understanding Attribution MethodsCode1
Robust Sensible Adversarial Learning of Deep Neural Networks for Image ClassificationCode0
Kernel Normalized Convolutional NetworksCode0
Set-based Meta-Interpolation for Few-Task Meta-Learning—0
Deep transfer learning for image classification: a survey—0
A Hardware-Aware Framework for Accelerating Neural Architecture Search Across Modalities—0
EXACT: How to Train Your AccuracyCode1
CLCNet: Rethinking of Ensemble Modeling with Classification Confidence NetworkCode1
TRT-ViT: TensorRT-oriented Vision Transformer—0
Bayesian Convolutional Neural Networks for Limited Data Hyperspectral Remote Sensing Image Classification—0
Masked Image Modeling with Denoising ContrastCode1
Incremental Learning with Differentiable Architecture and Forgetting Search—0
A graph-transformer for whole slide image classificationCode1
Semi-Supervised Learning for Image Classification using Compact Networks in the BioMedical Context—0
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All datasetsImageNetCIFAR-10CIFAR-100STL-10ObjectNetMNISTSVHNiNaturalist 2018ImageNet ReaLFlowers-102Clothing1Mmini WebVision 1.0

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
5Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2—Unverified
6DaViT-HTop 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
10RevCol-HTop 1 Accuracy90—Unverified