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 7251–7275 of 10420 papers

TitleStatusHype
Sparsely-gated Mixture-of-Expert Layers for CNN Interpretability—0
Panda or not Panda? Understanding Adversarial Attacks with Interactive Visualization—0
Is my Driver Observation Model Overconfident? Input-guided Calibration Networks for Reliable and Interpretable Confidence Estimates—0
Is More Data All You Need? A Causal Exploration—0
Is Label Smoothing Truly Incompatible with Knowledge Distillation: An Empirical Study—0
Parallel Rectangle Flip Attack: A Query-based Black-box Attack against Object Detection—0
Deeply Coupled Auto-encoder Networks for Cross-view Classification—0
Less is more: Selecting informative and diverse subsets with balancing constraints—0
Is it all a cluster game? -- Exploring Out-of-Distribution Detection based on Clustering in the Embedding Space—0
Parameter Efficient Fine-tuning via Cross Block Orchestration for Segment Anything Model—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 Generative Modeling-based Stylization Necessary for Domain Adaptation in Regression Tasks?—0
DeepLogo: Hitting Logo Recognition with the Deep Neural Network Hammer—0
Balancing Average and Worst-case Accuracy in Multitask Learning—0
A Multi-class Approach -- Building a Visual Classifier based on Textual Descriptions using Zero-Shot Learning—0
Is forgetting less a good inductive bias for forward transfer?—0
I See Dead People: Gray-Box Adversarial Attack on Image-To-Text Models—0
Parameter Re-Initialization through Cyclical Batch Size Schedules—0
Deep learning for image segmentation: veritable or overhyped?—0
IrisNet: Deep Learning for Automatic and Real-time Tongue Contour Tracking in Ultrasound Video Data using Peripheral Vision—0
Investigating the Robustness of Vision Transformers against Label Noise in Medical Image Classification—0
Investigating the Potential of Auxiliary-Classifier GANs for Image Classification in Low Data Regimes—0
CNNs for JPEGs: A Study in Computational Cost—0
Investigating the Catastrophic Forgetting in Multimodal Large Language Models—0
Investigating Calibration and Corruption Robustness of Post-hoc Pruned Perception CNNs: An Image Classification Benchmark Study—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
5DaViT-HTop 1 Accuracy90.2—Unverified
6Meta Pseudo Labels (EfficientNet-L2)Top 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
10Meta Pseudo Labels (EfficientNet-B6-Wide)Top 1 Accuracy90—Unverified