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 10761100 of 10420 papers

TitleStatusHype
BCN: Batch Channel Normalization for Image ClassificationCode1
DocXClassifier: High Performance Explainable Deep Network for Document Image ClassificationCode1
Do Deep Networks Transfer Invariances Across Classes?Code1
AIO-P: Expanding Neural Performance Predictors Beyond Image ClassificationCode1
Making Convolutional Networks Shift-Invariant AgainCode1
DO-Conv: Depthwise Over-parameterized Convolutional LayerCode1
Does VLM Classification Benefit from LLM Description Semantics?Code1
Domain-Adversarial Training of Neural NetworksCode1
AIDeveloper: deep learning image classification in life science and beyondCode1
Bayesian Optimization Meets Self-DistillationCode1
DKDFN: Domain Knowledge-Guided deep collaborative fusion network for multimodal unitemporal remote sensing land cover classificationCode1
A Hybrid Neural Coding Approach for Pattern Recognition with Spiking Neural NetworksCode1
DLME: Deep Local-flatness Manifold EmbeddingCode1
DLTTA: Dynamic Learning Rate for Test-time Adaptation on Cross-domain Medical ImagesCode1
Bayesian Model-Agnostic Meta-LearningCode1
Boosting Memory Efficiency in Transfer Learning for High-Resolution Medical Image ClassificationCode1
Bayesian Neural Network Priors RevisitedCode1
Bayesian continual learning and forgetting in neural networksCode1
ActMAD: Activation Matching to Align Distributions for Test-Time-TrainingCode1
Boosting Co-teaching with Compression Regularization for Label NoiseCode1
DMT-JEPA: Discriminative Masked Targets for Joint-Embedding Predictive ArchitectureCode1
Domain Generalization by Learning and Removing Domain-specific FeaturesCode1
Dynamic Graph Message Passing NetworksCode1
batchboost: regularization for stabilizing training with resistance to underfitting & overfittingCode1
Divergences in Color Perception between Deep Neural Networks and HumansCode1
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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