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 5101–5150 of 10420 papers

TitleStatusHype
PeCo: Perceptual Codebook for BERT Pre-training of Vision TransformersCode1
Improved Fine-Tuning by Better Leveraging Pre-Training Data—0
Spatial-context-aware deep neural network for multi-class image classification—0
MorphMLP: An Efficient MLP-Like Backbone for Spatial-Temporal Representation LearningCode0
Multi-label Iterated Learning for Image Classification with Label AmbiguityCode0
AutoDC: Automated data-centric processingCode1
Inducing Functions through Reinforcement Learning without Task Specification—0
CoDiM: Learning with Noisy Labels via Contrastive Semi-Supervised Learning—0
Using mixup as regularization and tuning hyper-parameters for ResNetsCode0
Focal and Global Knowledge Distillation for DetectorsCode1
Learning Consistent Deep Generative Models from Sparsely Labeled Data—0
Linearised Laplace Inference in Networks with Normalisation Layers and the Neural g-Prior—0
Metamorphic Adversarial Detection Pipeline for Face Recognition Systems—0
Revisiting Adversarial Robustness of Classifiers With a Reject Option—0
Broad Adversarial Training with Data Augmentation in the Output Space—0
DBIA: Data-free Backdoor Injection Attack against Transformer NetworksCode0
FedCV: A Federated Learning Framework for Diverse Computer Vision TasksCode1
MetaFormer Is Actually What You Need for VisionCode2
Adversarial Examples on Segmentation Models Can be Easy to Transfer—0
Nanorobot queue: Cooperative treatment of cancer based on team member communication and image processing—0
Deep Learning Based Automated COVID-19 Classification from Computed Tomography ImagesCode0
SSR: An Efficient and Robust Framework for Learning with Unknown Label NoiseCode1
MiNet: A Convolutional Neural Network for Identifying and Categorising Minerals—0
Semi-Supervised Vision TransformersCode1
Florence: A New Foundation Model for Computer VisionCode1
XnODR and XnIDR: Two Accurate and Fast Fully Connected Layers For Convolutional Neural NetworksCode0
Are Vision Transformers Robust to Patch Perturbations?—0
Discrete Representations Strengthen Vision Transformer RobustnessCode0
Medical Knowledge-Guided Deep Learning for Imbalanced Medical Image Classification—0
FBNetV5: Neural Architecture Search for Multiple Tasks in One Run—0
Combined Scaling for Zero-shot Transfer Learning—0
Rethinking Query, Key, and Value Embedding in Vision Transformer under Tiny Model Constraints—0
A 3D 2D convolutional Neural Network Model for Hyperspectral Image Classification—0
Grounded Situation Recognition with TransformersCode1
Understanding Training-Data Leakage from Gradients in Neural Networks for Image ClassificationCode0
Benchmarking and scaling of deep learning models for land cover image classificationCode1
COVID-19 Detection on Chest X-Ray Images: A comparison of CNN architectures and ensemblesCode0
Swin Transformer V2: Scaling Up Capacity and ResolutionCode1
Fairness Testing of Deep Image Classification with Adequacy Metrics—0
ReCLIP: A Strong Zero-Shot Baseline for Referring Expression Comprehension—0
Two-step adversarial debiasing with partial learning -- medical image case-studies—0
Document AI: Benchmarks, Models and Applications—0
Detecting AutoAttack Perturbations in the Frequency DomainCode1
Improved Robustness of Vision Transformer via PreLayerNorm in Patch Embedding—0
Learning with convolution and pooling operations in kernel methods—0
LiT: Zero-Shot Transfer with Locked-image text TuningCode1
iBOT: Image BERT Pre-Training with Online TokenizerCode1
Attention Mechanisms in Computer Vision: A SurveyCode2
Learning Data Teaching Strategies Via Knowledge Tracing—0
Image Classification with Consistent Supporting Evidence—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