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 6026–6050 of 10420 papers

TitleStatusHype
An Empirical Study of Adder Neural Networks for Object Detection—0
ViR:the Vision Reservoir—0
A Fistful of Words: Learning Transferable Visual Models from Bag-of-Words Supervision—0
Deep Curriculum Learning for PolSAR Image Classification—0
Virtuoso: Video-based Intelligence for real-time tuning on SOCs—0
Latent Time Neural Ordinary Differential Equations—0
Improving Robustness and Uncertainty Modelling in Neural Ordinary Differential Equations—0
AED: An black-box NLP classifier model attacker—0
Dynamically Stable Poincaré Embeddings for Neural Manifolds—0
Offloading Algorithms for Maximizing Inference Accuracy on Edge Device Under a Time Constraint—0
Cross-Part Learning for Fine-Grained Image ClassificationCode0
Encoding Hierarchical Information in Neural Networks helps in Subpopulation Shift—0
Learning with Label Noise for Image Retrieval by Selecting Interactions—0
A Vision-based Solution for Track Misalignment Detection—0
General Greedy De-bias LearningCode0
Denoised Labels for Financial Time-Series Data via Self-Supervised Learning—0
Zero-shot and Few-shot Learning with Knowledge Graphs: A Comprehensive Survey—0
Soundify: Matching Sound Effects to Video—0
Rank4Class: A Ranking Formulation for Multiclass Classification—0
Interpretable and Interactive Deep Multiple Instance Learning for Dental Caries Classification in Bitewing X-raysCode0
A Simple Single-Scale Vision Transformer for Object Localization and Instance SegmentationCode0
Classification of diffraction patterns using a convolutional neural network in single particle imaging experiments performed at X-ray free-electron lasers—0
Learning Interpretable Models Through Multi-Objective Neural Architecture SearchCode0
Use Image Clustering to Facilitate Technology Assisted Review—0
How to augment your ViTs? Consistency loss and StyleAug, a random style transfer augmentation—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
10Meta Pseudo Labels (EfficientNet-B6-Wide)Top 1 Accuracy90—Unverified