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 3651–3700 of 10419 papers

TitleStatusHype
Feature Weaken: Vicinal Data Augmentation for Classification—0
Personalized Federated Learning with Hidden Information on Personalized Prior—0
Towards Adversarial Robustness of Deep Vision Algorithms—0
Non-Coherent Over-the-Air Decentralized Gradient Descent—0
TensAIR: Real-Time Training of Neural Networks from Data-streamsCode0
Invariant Learning via Diffusion Dreamed Distribution Shifts—0
Vision Transformers in Medical Imaging: A Review—0
Hyperbolic Sliced-Wasserstein via Geodesic and Horospherical ProjectionsCode0
A Transformer Framework for Data Fusion and Multi-Task Learning in Smart CitiesCode0
Contrastive Losses Are Natural Criteria for Unsupervised Video SummarizationCode1
Efficient Feature Compression for Edge-Cloud SystemsCode0
FedFA: Federated Learning with Feature Anchors to Align Features and Classifiers for Heterogeneous DataCode1
Data-Centric Debugging: mitigating model failures via targeted data collection—0
Towards All-in-one Pre-training via Maximizing Multi-modal Mutual InformationCode1
DeepVoxNet2: Yet another CNN frameworkCode1
Improving the Computer-Aided Estimation of Ulcerative Colitis Severity According to Mayo Endoscopic Score by Using Regression-Based Deep LearningCode1
A Stable, Fast, and Fully Automatic Learning Algorithm for Predictive Coding Networks—0
Scalar Invariant Networks with Zero Bias—0
Masked Reconstruction Contrastive Learning with Information Bottleneck Principle—0
Probabilistic Deep Metric Learning for Hyperspectral Image ClassificationCode0
Identifying Spurious Correlations and Correcting them with an Explanation-based Learning—0
Local Magnification for Data and Feature Augmentation—0
Bayesian Federated Neural Matching that Completes Full Information—0
Will Large-scale Generative Models Corrupt Future Datasets?Code0
Federated Adaptive Prompt Tuning for Multi-Domain Collaborative LearningCode1
VCI-LSTM: Vector Choquet Integral-based Long Short-Term Memory—0
Robust Deep Learning for Autonomous DrivingCode1
Interpreting Bias in the Neural Networks: A Peek Into Representational Similarity—0
PKCAM: Previous Knowledge Channel Attention ModuleCode1
EVA: Exploring the Limits of Masked Visual Representation Learning at ScaleCode0
Fcaformer: Forward Cross Attention in Hybrid Vision TransformerCode1
Bayesian Layer Graph Convolutioanl Network for Hyperspetral Image Classification—0
SA-DPSGD: Differentially Private Stochastic Gradient Descent based on Simulated Annealing—0
Sign Language to Text Conversion in Real Time using Transfer Learning—0
Perceptual Video Coding for Machines via Satisfied Machine Ratio ModelingCode1
Mining Unseen Classes via Regional Objectness: A Simple Baseline for Incremental SegmentationCode1
Enhancing Few-shot Image Classification with Cosine TransformerCode1
Far Away in the Deep Space: Dense Nearest-Neighbor-Based Out-of-Distribution DetectionCode1
MultiCrossViT: Multimodal Vision Transformer for Schizophrenia Prediction using Structural MRI and Functional Network Connectivity Data—0
Multi-Epoch Matrix Factorization Mechanisms for Private Machine Learning—0
AltCLIP: Altering the Language Encoder in CLIP for Extended Language CapabilitiesCode4
Depth and Representation in Vision ModelsCode0
A Comprehensive Survey of Transformers for Computer Vision—0
Token Transformer: Can class token help window-based transformer build better long-range interactions?—0
Equivariance with Learned Canonicalization Functions—0
Dual Complementary Dynamic Convolution for Image Recognition—0
REVEL Framework to measure Local Linear Explanations for black-box models: Deep Learning Image Classification case of studyCode0
PAD-Net: An Efficient Framework for Dynamic NetworksCode1
InternImage: Exploring Large-Scale Vision Foundation Models with Deformable ConvolutionsCode4
MGiaD: Multigrid in all dimensions. Efficiency and robustness by coarsening in resolution and channel dimensions—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