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

Showing 88018850 of 10420 papers

TitleStatusHype
Compositional Model based Fisher Vector Coding for Image ClassificationCode0
Quantitative Analysis of Primary Attribution Explainable Artificial Intelligence Methods for Remote Sensing Image ClassificationCode0
Drop-Activation: Implicit Parameter Reduction and Harmonic RegularizationCode0
Residual and Plain Convolutional Neural Networks for 3D Brain MRI ClassificationCode0
Outside the Box: Abstraction-Based Monitoring of Neural NetworksCode0
A Twofold Siamese Network for Real-Time Object TrackingCode0
Overcoming Distribution Mismatch in Quantizing Image Super-Resolution NetworksCode0
Complementing Representation Deficiency in Few-shot Image Classification: A Meta-Learning ApproachCode0
Quantization NetworksCode0
Competing Ratio Loss for Discriminative Multi-class Image ClassificationCode0
Hybrid Macro/Micro Level Backpropagation for Training Deep Spiking Neural NetworksCode0
Overcoming Long-term Catastrophic Forgetting through Adversarial Neural Pruning and Synaptic ConsolidationCode0
A Tunable Robust Pruning Framework Through Dynamic Network Rewiring of DNNsCode0
Residual Attention Network for Image ClassificationCode0
Reweighting Augmented Samples by Minimizing the Maximal Expected LossCode0
Attribute-Guided Multi-Level Attention Network for Fine-Grained Fashion RetrievalCode0
Diverse Gaussian Noise Consistency Regularization for Robustness and Uncertainty CalibrationCode0
Mish: A Self Regularized Non-Monotonic Activation FunctionCode0
HybridSN: Exploring 3D-2D CNN Feature Hierarchy for Hyperspectral Image ClassificationCode0
Comparison Knowledge Translation for Generalizable Image ClassificationCode0
Attribute-based Visual Reprogramming for Image Classification with CLIPCode0
DeMansia: Mamba Never Forgets Any TokensCode0
HyenaPixel: Global Image Context with ConvolutionsCode0
DPA: Dual Prototypes Alignment for Unsupervised Adaptation of Vision-Language ModelsCode0
Comparing the Efficacy of Fine-Tuning and Meta-Learning for Few-Shot Policy ImitationCode0
Mitigating Adversarial Effects Through RandomizationCode0
Do Vision-Language Foundational models show Robust Visual Perception?Code0
Mitigating belief projection in explainable artificial intelligence via Bayesian TeachingCode0
Do Users Benefit From Interpretable Vision? A User Study, Baseline, And DatasetCode0
Doubly Robust Self-TrainingCode0
HyperbolicLR: Epoch insensitive learning rate schedulerCode0
Hyperbolic Sliced-Wasserstein via Geodesic and Horospherical ProjectionsCode0
Rewriting the Budget: A General Framework for Black-Box Attacks Under Cost AsymmetryCode0
Comparative Study Between Distance Measures On Supervised Optimum-Path Forest ClassificationCode0
Do Perceptually Aligned Gradients Imply Adversarial Robustness?Code0
HyperDID: Hyperspectral Intrinsic Image Decomposition with Deep Feature EmbeddingCode0
Quantized Neural Networks via -1, +1 Encoding Decomposition and AccelerationCode0
Don't Look into the Sun: Adversarial Solarization Attacks on Image ClassifiersCode0
Accelerating Malware Classification: A Vision Transformer SolutionCode0
Quantum algorithms for SVD-based data representation and analysisCode0
Hyperparameter Ensembles for Robustness and Uncertainty QuantificationCode0
RSI-CB: A Large Scale Remote Sensing Image Classification Benchmark via Crowdsource DataCode0
Attentive NormalizationCode0
Saccader: Improving Accuracy of Hard Attention Models for VisionCode0
Hyper-Process Model: A Zero-Shot Learning algorithm for Regression Problems based on Shape AnalysisCode0
Don't Forget to Sign the Gradients!Code0
Robustness Stress Testing in Medical Image ClassificationCode0
Comparative Evaluation of Clustered Federated Learning MethodsCode0
Do not trust what you trust: Miscalibration in Semi-supervised LearningCode0
PaCKD: Pattern-Clustered Knowledge Distillation for Compressing Memory Access Prediction ModelsCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CoCa (finetuned)Top 1 Accuracy91Unverified
2Model soups (BASIC-L)Top 1 Accuracy90.98Unverified
3Model soups (ViT-G/14)Top 1 Accuracy90.94Unverified
4DaViT-GTop 1 Accuracy90.4Unverified
5Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2Unverified
6DaViT-HTop 1 Accuracy90.2Unverified
7SwinV2-GTop 1 Accuracy90.17Unverified
8MAWS (ViT-6.5B)Top 1 Accuracy90.1Unverified
9Florence-CoSwin-HTop 1 Accuracy90.05Unverified
10RevCol-HTop 1 Accuracy90Unverified