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

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Showing 2751–2800 of 10419 papers

TitleStatusHype
A CNN with Noise Inclined Module and Denoise Framework for Hyperspectral Image ClassificationCode0
Bounded logit attention: Learning to explain image classifiersCode0
Inception-inspired LSTM for Next-frame Video PredictionCode0
A Deeper Look into Convolutions via Eigenvalue-based PruningCode0
Understanding Intrinsic Robustness Using Label UncertaintyCode0
Born Again Neural NetworksCode0
Bootstrapping the Relationship Between Images and Their Clean and Noisy LabelsCode0
Boosting with Lexicographic Programming: Addressing Class Imbalance without Cost TuningCode0
3D CNN with Localized Residual Connections for Hyperspectral Image ClassificationCode0
Improvising the Learning of Neural Networks on Hyperspherical ManifoldCode0
Increasing-Margin Adversarial (IMA) Training to Improve Adversarial Robustness of Neural NetworksCode0
Improving the Gating Mechanism of Recurrent Neural NetworksCode0
Improving the repeatability of deep learning models with Monte Carlo dropoutCode0
A Gradient Boosting Approach for Training Convolutional and Deep Neural NetworksCode0
Improving the Efficiency of Human-in-the-Loop Systems: Adding Artificial to Human ExpertsCode0
An empirical study on the effects of different types of noise in image classification tasksCode0
Improving singing voice separation with the Wave-U-Net using Minimum Hyperspherical EnergyCode0
Boosting Occluded Image Classification via Subspace Decomposition Based Estimation of Deep FeaturesCode0
Attention Augmented Convolutional NetworksCode0
Improving Shift Invariance in Convolutional Neural Networks with Translation Invariant Polyphase SamplingCode0
Improving the trustworthiness of image classification models by utilizing bounding-box annotationsCode0
An Empirical Study Of Self-supervised Learning Approaches For Object Detection With TransformersCode0
Improving Prototypical Visual Explanations with Reward Reweighing, Reselection, and RetrainingCode0
Improving Random-Sampling Neural Architecture Search by Evolving the Proxy Search SpaceCode0
Improving robustness to corruptions with multiplicative weight perturbationsCode0
Boosting High Resolution Image Classification with Scaling-up TransformersCode0
Improving Pairwise Ranking for Multi-label Image ClassificationCode0
Improving Nonlinear Projection Heads using Pretrained Autoencoder EmbeddingsCode0
Improving Pre-Trained Weights Through Meta-Heuristics Fine-TuningCode0
Improving Transferability of Adversarial Examples with Input DiversityCode0
InterpNET: Neural Introspection for Interpretable Deep LearningCode0
Learning to Learn from Noisy Labeled DataCode0
Acne Severity Grading on Face Images via Extraction and Guidance of Prior KnowledgeCode0
SynerMix: Synergistic Mixup Solution for Enhanced Intra-Class Cohesion and Inter-Class Separability in Image ClassificationCode0
Boosting Ensemble Accuracy by Revisiting Ensemble Diversity MetricsCode0
Boosting Domain Incremental Learning: Selecting the Optimal Parameters is All You NeedCode0
Improving Intervention Efficacy via Concept Realignment in Concept Bottleneck ModelsCode0
Improving Generalization and Convergence by Enhancing Implicit RegularizationCode0
An Empirical Investigation of Randomized Defenses against Adversarial AttacksCode0
Boosting Deep Ensemble Performance with Hierarchical PruningCode0
Addressing Small and Imbalanced Medical Image Datasets Using Generative Models: A Comparative Study of DDPM and PGGANs with Random and Greedy K SamplingCode0
Improving Generalization of Batch Whitening by Convolutional Unit OptimizationCode0
Improving k-Means Clustering Performance with Disentangled Internal RepresentationsCode0
Improving Ensemble Distillation With Weight Averaging and Diversifying PerturbationCode0
Improving Fairness in Image Classification via SketchingCode0
Boosting Adversarial Transferability across Model Genus by Deformation-Constrained WarpingCode0
1st Place Solution for ECCV 2022 OOD-CV Challenge Image Classification TrackCode0
Improving Deep Neural Network Random Initialization Through Neuronal RewiringCode0
Improving Generalizability of Kolmogorov-Arnold Networks via Error-Correcting Output CodesCode0
Improving Long-tailed Object Detection with Image-Level Supervision by Multi-Task Collaborative LearningCode0
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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