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 40764100 of 10420 papers

TitleStatusHype
Hyperspectral Image Classification in the Presence of Noisy LabelsCode0
Hyperspectral Image Classification via Transformer-based Spectral-Spatial Attention Decoupling and Adaptive GatingCode0
Hyperparameter Ensembles for Robustness and Uncertainty QuantificationCode0
Hyper-Process Model: A Zero-Shot Learning algorithm for Regression Problems based on Shape AnalysisCode0
Hyperspectral image classification via a random patches networkCode0
Compressing Vision Transformers for Low-Resource Visual LearningCode0
The Pitfalls and Promise of Conformal Inference Under Adversarial AttacksCode0
iCAR: Bridging Image Classification and Image-text Alignment for Visual RecognitionCode0
Image classification and retrieval with random depthwise signed convolutional neural networksCode0
Few and Fewer: Learning Better from Few Examples Using Fewer Base ClassesCode0
Few-Class Arena: A Benchmark for Efficient Selection of Vision Models and Dataset Difficulty MeasurementCode0
Cross-domain Open-world DiscoveryCode0
A self-interpretable module for deep image classification on small dataCode0
Cross-Domain Image Classification through Neural-Style Transfer Data AugmentationCode0
The Treasure beneath Convolutional Layers: Cross-convolutional-layer Pooling for Image ClassificationCode0
Feature Extractor Stacking for Cross-domain Few-shot LearningCode0
The Unmet Promise of Synthetic Training Images: Using Retrieved Real Images Performs BetterCode0
Few-shot Fine-grained Image Classification via Multi-Frequency Neighborhood and Double-cross ModulationCode0
A Large-scale Study of Representation Learning with the Visual Task Adaptation BenchmarkCode0
Attention Gated Networks: Learning to Leverage Salient Regions in Medical ImagesCode0
HyperbolicLR: Epoch insensitive learning rate schedulerCode0
Hyperbolic Sliced-Wasserstein via Geodesic and Horospherical ProjectionsCode0
Cross-domain Contrastive Learning for Unsupervised Domain AdaptationCode0
On Biases in a UK Biobank-based Retinal Image Classification ModelCode0
HybridSN: Exploring 3D-2D CNN Feature Hierarchy for Hyperspectral Image ClassificationCode0
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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