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 6126–6150 of 10420 papers

TitleStatusHype
Explainability-aided Domain Generalization for Image Classification—0
Towards Self-Adaptive Metric Learning On the Fly—0
Unconstrained Face Recognition using ASURF and Cloud-Forest Classifier optimized with VLAD—0
Diverse Gaussian Noise Consistency Regularization for Robustness and Uncertainty CalibrationCode0
AAformer: Auto-Aligned Transformer for Person Re-Identification—0
LiftPool: Bidirectional ConvNet Pooling—0
LeViT: a Vision Transformer in ConvNet's Clothing for Faster InferenceCode1
Estimating the Generalization in Deep Neural Networks via Sparsity—0
Plot2API: Recommending Graphic API from Plot via Semantic Parsing Guided Neural NetworkCode0
Defending Against Image Corruptions Through Adversarial Augmentations—0
Network Quantization with Element-wise Gradient ScalingCode1
Keep Learning: Self-supervised Meta-learning for Learning from Inference—0
EfficientNetV2: Smaller Models and Faster TrainingCode3
Effect of Radiology Report Labeler Quality on Deep Learning Models for Chest X-Ray Interpretation—0
Remote Sensing Image Classification with the SEN12MS DatasetCode1
The Effects of Spectral Dimensionality Reduction on Hyperspectral Pixel Classification: A Case Study—0
Anytime Dense Prediction with Confidence AdaptivityCode1
Is Label Smoothing Truly Incompatible with Knowledge Distillation: An Empirical Study—0
SpectralNET: Exploring Spatial-Spectral WaveletCNN for Hyperspectral Image ClassificationCode1
On the Robustness of Vision Transformers to Adversarial ExamplesCode1
Spectral decoupling allows training transferable neural networks in medical imaging—0
A Novel Deep ML Architecture by Integrating Visual Simultaneous Localization and Mapping (vSLAM) into Mask R-CNN for Real-time Surgical Video Analysis—0
Joint Learning of Neural Transfer and Architecture Adaptation for Image Recognition—0
Going deeper with Image TransformersCode1
Fixing the Teacher-Student Knowledge Discrepancy in Distillation—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
10RevCol-HTop 1 Accuracy90—Unverified