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 6901–6950 of 10420 papers

TitleStatusHype
Sampling-free Variational Inference for Neural Networks with Multiplicative Activation Noise—0
CrossoverScheduler: Overlapping Multiple Distributed Training Applications in a Crossover Manner—0
Efficient Sparse Artificial Neural Networks—0
Uncertainty-guided Model Generalization to Unseen Domains—0
Learnable Companding Quantization for Accurate Low-bit Neural Networks—0
Interleaving Learning, with Application to Neural Architecture Search—0
Evaluating COPY-BLEND Augmentation for Low Level Vision Tasks—0
Why flatness does and does not correlate with generalization for deep neural networks—0
TransMed: Transformers Advance Multi-modal Medical Image Classification—0
Cut-Thumbnail: A Novel Data Augmentation for Convolutional Neural NetworkCode0
Improving Global Adversarial Robustness Generalization With Adversarially Trained GAN—0
Efficient Model Performance Estimation via Feature Histories—0
A Retrospective Approximation Approach for Smooth Stochastic Optimization—0
End-to-end optimized image compression for multiple machine tasks—0
LongReMix: Robust Learning with High Confidence Samples in a Noisy Label EnvironmentCode0
Contextual Dropout: An Efficient Sample-Dependent Dropout ModuleCode0
Selective Replay Enhances Learning in Online Continual Analogical ReasoningCode0
SCRIB: Set-classifier with Class-specific Risk Bounds for Blackbox Models—0
Unified Robust Training for Graph NeuralNetworks against Label Noise—0
Don't Forget to Sign the Gradients!Code0
Measuring Model Biases in the Absence of Ground Truth—0
Unsupervised Domain Adaptation for Image Classification via Structure-Conditioned Adversarial Learning—0
QAIR: Practical Query-efficient Black-Box Attacks for Image Retrieval—0
Redundant Information Neural Estimation—0
Hard-label Manifolds: Unexpected Advantages of Query Efficiency for Finding On-manifold Adversarial Examples—0
Vanishing Twin GAN: How training a weak Generative Adversarial Network can improve semi-supervised image classification—0
Learning Invariant Representations across Domains and Tasks—0
An Alternative Practice of Tropical Convolution to Traditional Convolutional Neural Networks—0
Comparison of Methods Generalizing Max- and Average-Pooling—0
Fast Adaptation with Linearized Neural Networks—0
Demystifying Batch Normalization in ReLU Networks: Equivalent Convex Optimization Models and Implicit Regularization—0
Improved Techniques for Quantizing Deep Networks with Adaptive Bit-Widths—0
A Structurally Regularized Convolutional Neural Network for Image Classification using Wavelet-based SubBand Decomposition—0
Self-supervised Pretraining of Visual Features in the Wild—0
Multiclass Burn Wound Image Classification Using Deep Convolutional Neural Networks—0
Diversifying Sample Generation for Accurate Data-Free Quantization—0
Brain Programming is Immune to Adversarial Attacks: Towards Accurate and Robust Image Classification using Symbolic Learning—0
Maximal function pooling with applications—0
Virus-MNIST: A Benchmark Malware Dataset—0
Improving Medical Image Classification with Label Noise Using Dual-uncertainty Estimation—0
Variational Laplace for Bayesian neural networks—0
Semi-supervised Learning for COVID-19 Image Classification via ResNet—0
Statistical Measures For Defining Curriculum Scoring FunctionCode0
Class Knowledge Overlay to Visual Feature Learning for Zero-Shot Image Classification—0
A Universal Model for Cross Modality Mapping by Relational Reasoning—0
Web Table Classification based on Visual Features—0
Robust Pollen Imagery Classification with Generative Modeling and Mixup Training—0
Visual Word Embedding for Text ClassificationCode0
Highly Efficient Representation and Active Learning Framework and Its Application to Imbalanced Medical Image Classification—0
Transfer Learning with Convolutional Neural Networks for Rainfall Detection in Single ImagesCode0
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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