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 13761400 of 10420 papers

TitleStatusHype
Topological Structure and Semantic Information Transfer Network for Cross-Scene Hyperspectral Image ClassificationCode1
Sparse MLP for Image Recognition: Is Self-Attention Really Necessary?Code1
Co-Correcting: Noise-tolerant Medical Image Classification via mutual Label CorrectionCode1
ConvMLP: Hierarchical Convolutional MLPs for VisionCode1
Knowledge Distillation Using Hierarchical Self-Supervision Augmented DistributionCode1
Less is More: Lighter and Faster Deep Neural Architecture for Tomato Leaf Disease ClassificationCode1
Robust fine-tuning of zero-shot modelsCode1
Automated detection of COVID-19 cases from chest X-ray images using deep neural network and XGBoostCode1
Diverse Sample Generation: Pushing the Limit of Generative Data-free QuantizationCode1
Semi-supervised Image Classification with Grad-CAM ConsistencyCode1
Morphence: Moving Target Defense Against Adversarial ExamplesCode1
Tune It or Don't Use It: Benchmarking Data-Efficient Image ClassificationCode1
Hire-MLP: Vision MLP via Hierarchical RearrangementCode1
MEDIC: A Multi-Task Learning Dataset for Disaster Image ClassificationCode1
Towards Fine-grained Image Classification with Generative Adversarial Networks and Facial Landmark DetectionCode1
Improving Object Detection by Label Assignment DistillationCode1
Tune it the Right Way: Unsupervised Validation of Domain Adaptation via Soft Neighborhood DensityCode1
Variable-Rate Deep Image Compression through Spatially-Adaptive Feature TransformCode1
PatchCleanser: Certifiably Robust Defense against Adversarial Patches for Any Image ClassifierCode1
Do Vision Transformers See Like Convolutional Neural Networks?Code1
Contextual Convolutional Neural NetworksCode1
spectrai: A deep learning framework for spectral dataCode1
EEEA-Net: An Early Exit Evolutionary Neural Architecture SearchCode1
Learning Transferable Parameters for Unsupervised Domain AdaptationCode1
SoK: How Robust is Image Classification Deep Neural Network Watermarking? (Extended Version)Code1
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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