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 11011125 of 10420 papers

TitleStatusHype
Domain Adaptation for Multi-label Image Classification: a Discriminator-free ApproachCode1
Domain Generalization by Learning and Removing Domain-specific FeaturesCode1
DocXClassifier: High Performance Explainable Deep Network for Document Image ClassificationCode1
DO-Conv: Depthwise Over-parameterized Convolutional LayerCode1
Do Deep Networks Transfer Invariances Across Classes?Code1
BCN: Batch Channel Normalization for Image ClassificationCode1
DMT-JEPA: Discriminative Masked Targets for Joint-Embedding Predictive ArchitectureCode1
Does VLM Classification Benefit from LLM Description Semantics?Code1
Domain Generalization via Gradient SurgeryCode1
Bayesian Optimization Meets Self-DistillationCode1
Active Token MixerCode1
DKDFN: Domain Knowledge-Guided deep collaborative fusion network for multimodal unitemporal remote sensing land cover classificationCode1
Diversify and Disambiguate: Learning From Underspecified DataCode1
Diversified in-domain synthesis with efficient fine-tuning for few-shot classificationCode1
DivideMix: Learning with Noisy Labels as Semi-supervised LearningCode1
DLME: Deep Local-flatness Manifold EmbeddingCode1
A graph-transformer for whole slide image classificationCode1
Bayesian Model-Agnostic Meta-LearningCode1
Bayesian continual learning and forgetting in neural networksCode1
Divergences in Color Perception between Deep Neural Networks and HumansCode1
Diverse Branch Block: Building a Convolution as an Inception-like UnitCode1
Distilling Visual Priors from Self-Supervised LearningCode1
Bayesian Neural Network Priors RevisitedCode1
Distribution Alignment: A Unified Framework for Long-tail Visual RecognitionCode1
AsymmNet: Towards ultralight convolution neural networks using asymmetrical bottlenecksCode1
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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