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 8401–8450 of 10420 papers

TitleStatusHype
Making Deep Neural Networks Robust to Label Noise: a Loss Correction ApproachCode0
Evaluating ResNeXt Model Architecture for Image ClassificationCode0
Language-biased image classification: evaluation based on semantic representationsCode0
Evaluating Generalization Ability of Convolutional Neural Networks and Capsule Networks for Image Classification via Top-2 ClassificationCode0
Making EfficientNet More Efficient: Exploring Batch-Independent Normalization, Group Convolutions and Reduced Resolution TrainingCode0
A Benchmark for Interpretability Methods in Deep Neural NetworksCode0
Making Reliable and Flexible Decisions in Long-tailed ClassificationCode0
Making Robust Generalizers Less Rigid with Loss ConcentrationCode0
Core Tokensets for Data-efficient Sequential Training of TransformersCode0
Generalizing Pooling Functions in Convolutional Neural Networks: Mixed, Gated, and TreeCode0
Evaluating Cell Type Inference in Vision Language Models Under Varying Visual ContextCode0
Generate, Annotate, and Learn: NLP with Synthetic TextCode0
Repaint: Improving the Generalization of Down-Stream Visual Tasks by Generating Multiple Instances of Training ExamplesCode0
On the Relationship between Self-Attention and Convolutional LayersCode0
Probabilistic Trust Intervals for Out of Distribution DetectionCode0
Cooperative Meta-Learning with Gradient AugmentationCode0
Generating customized prompts for Zero-Shot Rare Event Medical Image Classification using LLMCode0
Convolution with even-sized kernels and symmetric paddingCode0
EVA: Exploring the Limits of Masked Visual Representation Learning at ScaleCode0
Revisiting Orthogonality Regularization: A Study for Convolutional Neural Networks in Image ClassificationCode0
EVA-CLIP-18B: Scaling CLIP to 18 Billion ParametersCode0
Convolution Based Spectral Partitioning Architecture for Hyperspectral Image ClassificationCode0
Generating Multi-Center Classifier via Conditional Gaussian DistributionCode0
Generating Natural Adversarial ExamplesCode0
Generating Natural Language Adversarial Examples through Probability Weighted Word SaliencyCode0
Convolutional Oriented Boundaries: From Image Segmentation to High-Level TasksCode0
Generating Relevant Counter-Examples from a Positive Unlabeled Dataset for Image ClassificationCode0
An Analysis of Unsupervised Pre-training in Light of Recent AdvancesCode0
EurNet: Efficient Multi-Range Relational Modeling of Spatial Multi-Relational DataCode0
Convolutional Oriented BoundariesCode0
Convolutional Neural Networks with Layer ReuseCode0
Manas: Mining Software Repositories to Assist AutoMLCode0
A CNN with Noise Inclined Module and Denoise Framework for Hyperspectral Image ClassificationCode0
Manifold Oblique Random Forests: Towards Closing the Gap on Convolutional Deep NetworksCode0
ETran: Energy-Based Transferability EstimationCode0
On the Robustness of Semantic Segmentation Models to Adversarial AttacksCode0
Estimating the Conformal Prediction Threshold from Noisy LabelsCode0
ScribbleGen: Generative Data Augmentation Improves Scribble-supervised Semantic SegmentationCode0
Automatic Data Augmentation via Invariance-Constrained LearningCode0
Estimated Depth Map Helps Image ClassificationCode0
Generative Image Translation for Data Augmentation in Colorectal Histopathology ImagesCode0
ESPNetv2: A Light-weight, Power Efficient, and General Purpose Convolutional Neural NetworkCode0
Automated Classification of Histopathology Images Using Transfer LearningCode0
Generative Max-Mahalanobis Classifiers for Image Classification, Generation and MoreCode0
Rethinking Robust Contrastive Learning from the Adversarial PerspectiveCode0
Generative Modeling Helps Weak Supervision (and Vice Versa)Code0
Error-free Training for Artificial Neural NetworkCode0
Replica Tree-based Federated Learning using Limited DataCode0
Convolutional Neural Networks for Global Human Settlements Mapping from Sentinel-2 Satellite ImageryCode0
Err on the Side of Texture: Texture Bias on Real DataCode0
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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