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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 9951–9975 of 10420 papers

TitleStatusHype
Investigating the Catastrophic Forgetting in Multimodal Large Language Models—0
Investigating the Potential of Auxiliary-Classifier GANs for Image Classification in Low Data Regimes—0
Investigating the Robustness of Vision Transformers against Label Noise in Medical Image Classification—0
IrisNet: Deep Learning for Automatic and Real-time Tongue Contour Tracking in Ultrasound Video Data using Peripheral Vision—0
Deep learning for image segmentation: veritable or overhyped?—0
I See Dead People: Gray-Box Adversarial Attack on Image-To-Text Models—0
Is forgetting less a good inductive bias for forward transfer?—0
Is Generative Modeling-based Stylization Necessary for Domain Adaptation in Regression Tasks?—0
Is the aspect ratio of cells important in deep learning? A robust comparison of deep learning methods for multi-scale cytopathology cell image classification: from convolutional neural networks to visual transformers—0
Is it all a cluster game? -- Exploring Out-of-Distribution Detection based on Clustering in the Embedding Space—0
Is Label Smoothing Truly Incompatible with Knowledge Distillation: An Empirical Study—0
Is More Data All You Need? A Causal Exploration—0
Is my Driver Observation Model Overconfident? Input-guided Calibration Networks for Reliable and Interpretable Confidence Estimates—0
Is network fragmentation a useful complexity measure?—0
Is Pretraining Necessary for Hyperspectral Image Classification?—0
IT^3: Idempotent Test-Time Training—0
Iterative Averaging in the Quest for Best Test Error—0
Iterative Attention Mining for Weakly Supervised Thoracic Disease Pattern Localization in Chest X-Rays—0
Iterative collaborative routing among equivariant capsules for transformation-robust capsule networks—0
Iterative Learning for Reliable Crowdsourcing Systems—0
Iterative Online Image Synthesis via Diffusion Model for Imbalanced Classification—0
Iterative Quantum Feature Maps—0
Iterative Self-Learning: Semi-Supervised Improvement to Dataset Volumes and Model Accuracy—0
Layer-wise Relevance Propagation for Echo State Networks applied to Earth System Variability—0
It's Not a Modality Gap: Characterizing and Addressing the Contrastive Gap—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