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 1801–1850 of 10419 papers

TitleStatusHype
Shape-Texture Debiased Neural Network TrainingCode1
Glance and Focus: a Dynamic Approach to Reducing Spatial Redundancy in Image ClassificationCode1
MoCo-CXR: MoCo Pretraining Improves Representation and Transferability of Chest X-ray ModelsCode1
Regularizing Neural Networks via Adversarial Model PerturbationCode1
Permuted AdaIN: Reducing the Bias Towards Global Statistics in Image ClassificationCode1
A Fully Tensorized Recurrent Neural NetworkCode1
Learning Binary Semantic Embedding for Histology Image Classification and RetrievalCode1
A Panda? No, It's a Sloth: Slowdown Attacks on Adaptive Multi-Exit Neural Network InferenceCode1
Rotate to Attend: Convolutional Triplet Attention ModuleCode1
A Data Set and a Convolutional Model for Iconography Classification in PaintingsCode1
Learning with Instance-Dependent Label Noise: A Sample Sieve ApproachCode1
Long-tailed Recognition by Routing Diverse Distribution-Aware ExpertsCode1
Supporting large-scale image recognition with out-of-domain samplesCode1
Bounding Boxes Are All We Need: Street View Image Classification via Context Encoding of Detected BuildingsCode1
Neural BootstrapperCode1
Contrastive Learning of Medical Visual Representations from Paired Images and TextCode1
MLRSNet: A Multi-label High Spatial Resolution Remote Sensing Dataset for Semantic Scene UnderstandingCode1
DVERGE: Diversifying Vulnerabilities for Enhanced Robust Generation of EnsemblesCode1
Attentional Feature FusionCode1
Asymmetric Loss For Multi-Label ClassificationCode1
Long-Tailed Classification by Keeping the Good and Removing the Bad Momentum Causal EffectCode1
HetSeq: Distributed GPU Training on Heterogeneous InfrastructureCode1
From Pixel to Patch: Synthesize Context-aware Features for Zero-shot Semantic SegmentationCode1
Adversarial Examples in Deep Learning for Multivariate Time Series RegressionCode1
Multiscale Context-Aware Ensemble Deep KELM for Efficient Hyperspectral Image ClassificationCode1
Multi-Modal Reasoning Graph for Scene-Text Based Fine-Grained Image Classification and RetrievalCode1
Stereopagnosia: Fooling Stereo Networks with Adversarial PerturbationsCode1
Searching for Low-Bit Weights in Quantized Neural NetworksCode1
MEAL V2: Boosting Vanilla ResNet-50 to 80%+ Top-1 Accuracy on ImageNet without TricksCode1
MoPro: Webly Supervised Learning with Momentum PrototypesCode1
A Visual Analytics Framework for Explaining and Diagnosing Transfer Learning ProcessesCode1
Puzzle Mix: Exploiting Saliency and Local Statistics for Optimal MixupCode1
Understanding the Role of Individual Units in a Deep Neural NetworkCode1
Region Comparison Network for Interpretable Few-shot Image ClassificationCode1
Stochastic-YOLO: Efficient Probabilistic Object Detection under Dataset ShiftsCode1
Improving Self-Organizing Maps with Unsupervised Feature ExtractionCode1
S3NAS: Fast NPU-aware Neural Architecture Search MethodologyCode1
Imbalanced Image Classification with Complement Cross EntropyCode1
Protect, Show, Attend and Tell: Empowering Image Captioning Models with Ownership ProtectionCode1
Self-Supervised Learning for Large-Scale Unsupervised Image ClusteringCode1
Joint Modeling of Chest Radiographs and Radiology Reports for Pulmonary Edema AssessmentCode1
Abstracting Deep Neural Networks into Concept Graphs for Concept Level InterpretabilityCode1
Contextual Diversity for Active LearningCode1
An Overview of Deep Learning Architectures in Few-Shot Learning DomainCode1
An Ensemble of Simple Convolutional Neural Network Models for MNIST Digit RecognitionCode1
More Diverse Means Better: Multimodal Deep Learning Meets Remote Sensing Imagery ClassificationCode1
Non-convex Learning via Replica Exchange Stochastic Gradient MCMCCode1
Adversarial Training with Fast Gradient Projection Method against Synonym Substitution based Text AttacksCode1
Graph Convolutional Networks for Hyperspectral Image ClassificationCode1
Shape Adaptor: A Learnable Resizing ModuleCode1
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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
5DaViT-HTop 1 Accuracy90.2—Unverified
6Meta Pseudo Labels (EfficientNet-L2)Top 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
10Meta Pseudo Labels (EfficientNet-B6-Wide)Top 1 Accuracy90—Unverified