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

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Showing 7126–7150 of 10420 papers

TitleStatusHype
Just Noticeable Difference for Machine Perception and Generation of Regularized Adversarial Images with Minimal Perturbation—0
Just Leaf It: Accelerating Diffusion Classifiers with Hierarchical Class Pruning—0
Ontology-based n-ball Concept Embeddings Informing Few-shot Image Classification—0
Deep Neural Network Approximation Theory—0
Judge Like a Real Doctor: Dual Teacher Sample Consistency Framework for Semi-supervised Medical Image Classification—0
Joint Source-Channel Coding for Channel-Adaptive Digital Semantic Communications—0
Joint Sensing and Task-Oriented Communications with Image and Wireless Data Modalities for Dynamic Spectrum Access—0
Deep Networks with Fast Retraining—0
Batch Calibration: Rethinking Calibration for In-Context Learning and Prompt Engineering—0
A Multi-Modal Multilingual Benchmark for Document Image Classification—0
OOD Augmentation May Be at Odds with Open-Set Recognition—0
OOD-CV-v2: An extended Benchmark for Robustness to Out-of-Distribution Shifts of Individual Nuisances in Natural Images—0
Achieving 3D Attention via Triplet Squeeze and Excitation Block—0
Recent Advances in Medical Image Classification—0
Joint Projection and Dictionary Learning using Low-rank Regularization and Graph Constraints—0
Joint Learning of Set Cardinality and State Distribution—0
Joint Learning of Neural Transfer and Architecture Adaptation for Image Recognition—0
Deep Multi-view Models for Glitch Classification—0
Joint Learning of Discriminative Low-dimensional Image Representations Based on Dictionary Learning and Two-layer Orthogonal Projections—0
Joint Intermodal and Intramodal Label Transfers for Extremely Rare or Unseen Classes—0
Deep Multi-View Learning using Neuron-Wise Correlation-Maximizing Regularizers—0
A Multi-Modal Federated Learning Framework for Remote Sensing Image Classification—0
Joint Hierarchical Category Structure Learning and Large-Scale Image Classification—0
Open Set Learning with Counterfactual Images—0
Deep Multi-Task Learning for Malware Image Classification—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