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 19261950 of 10420 papers

TitleStatusHype
Sliced Recursive TransformerCode1
A Contrastive Distillation Approach for Incremental Semantic Segmentation in Aerial ImagesCode1
DCN-T: Dual Context Network with Transformer for Hyperspectral Image ClassificationCode1
SMPConv: Self-moving Point Representations for Continuous ConvolutionCode1
Perceptual Video Coding for Machines via Satisfied Machine Ratio ModelingCode1
Delving into Out-of-Distribution Detection with Medical Vision-Language ModelsCode1
Soft Augmentation for Image ClassificationCode1
A Spectral-Spatial-Dependent Global Learning Framework for Insufficient and Imbalanced Hyperspectral Image ClassificationCode1
Demonstrating the Efficacy of Kolmogorov-Arnold Networks in Vision TasksCode1
Combating Label Noise in Deep Learning Using AbstentionCode1
Arch-Net: Model Distillation for Architecture Agnostic Model DeploymentCode1
Combating noisy labels by agreement: A joint training method with co-regularizationCode1
Sparse Concept Bottleneck Models: Gumbel Tricks in Contrastive LearningCode1
Sparse MLP for Image Recognition: Is Self-Attention Really Necessary?Code1
Sparse Networks from Scratch: Faster Training without Losing PerformanceCode1
SparseSwin: Swin Transformer with Sparse Transformer BlockCode1
Sparse Weight Activation TrainingCode1
Spatially Consistent Representation LearningCode1
DenoiseRep: Denoising Model for Representation LearningCode1
SPECIAL: Zero-shot Hyperspectral Image Classification With CLIPCode1
spectrai: A deep learning framework for spectral dataCode1
SpectralNET: Exploring Spatial-Spectral WaveletCNN for Hyperspectral Image ClassificationCode1
Spectral-Spatial Global Graph Reasoning for Hyperspectral Image ClassificationCode1
Combining GANs and AutoEncoders for Efficient Anomaly DetectionCode1
DeiT III: Revenge of the ViTCode1
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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