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 21762200 of 10420 papers

TitleStatusHype
AutoAssist: A Framework to Accelerate Training of Deep Neural NetworksCode1
Incorporating Convolution Designs into Visual TransformersCode1
AFN: Adaptive Fusion Normalization via an Encoder-Decoder FrameworkCode1
Contrasting Intra-Modal and Ranking Cross-Modal Hard Negatives to Enhance Visio-Linguistic Compositional UnderstandingCode1
Less is More: Pay Less Attention in Vision TransformersCode1
A Survey: Deep Learning for Hyperspectral Image Classification with Few Labeled SamplesCode1
Leveraging Cross-Modal Neighbor Representation for Improved CLIP ClassificationCode1
Increasing Model Capacity for Free: A Simple Strategy for Parameter Efficient Fine-tuningCode1
Decoupled Weight Decay RegularizationCode1
Contrastive Deep SupervisionCode1
LFI-CAM: Learning Feature Importance for Better Visual ExplanationCode1
InfoMatch: Entropy Neural Estimation for Semi-Supervised Image ClassificationCode1
Deep AutoAugmentCode1
A Survey of Classical And Quantum Sequence ModelsCode1
LightViT: Towards Light-Weight Convolution-Free Vision TransformersCode1
No Routing Needed Between CapsulesCode1
Contrastive Learning Improves Model Robustness Under Label NoiseCode1
Instance Localization for Self-supervised Detection PretrainingCode1
Contrastive Learning of Generalized Game RepresentationsCode1
InceptionMamba: An Efficient Hybrid Network with Large Band Convolution and Bottleneck MambaCode1
Contrastive Learning of Medical Visual Representations from Paired Images and TextCode1
Deep Complex NetworksCode1
ConvMLP: Hierarchical Convolutional MLPs for VisionCode1
Locally Shifted Attention With Early Global IntegrationCode1
Deep Prototypical Networks with Hybrid Residual Attention for Hyperspectral Image ClassificationCode1
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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
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