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 901925 of 10419 papers

TitleStatusHype
IncepFormer: Efficient Inception Transformer with Pyramid Pooling for Semantic SegmentationCode1
Improving Zero-shot Generalization and Robustness of Multi-modal ModelsCode1
BEV-LGKD: A Unified LiDAR-Guided Knowledge Distillation Framework for BEV 3D Object DetectionCode1
Hyperbolic Contrastive Learning for Visual Representations beyond ObjectsCode1
ResFormer: Scaling ViTs with Multi-Resolution TrainingCode1
Bi-directional Feature Reconstruction Network for Fine-Grained Few-Shot Image ClassificationCode1
AIO-P: Expanding Neural Performance Predictors Beyond Image ClassificationCode1
Curriculum Temperature for Knowledge DistillationCode1
Class Adaptive Network CalibrationCode1
RankDNN: Learning to Rank for Few-shot LearningCode1
A Call to Reflect on Evaluation Practices for Failure Detection in Image ClassificationCode1
Cross-Domain Ensemble Distillation for Domain GeneralizationCode1
SVFormer: Semi-supervised Video Transformer for Action RecognitionCode1
ActMAD: Activation Matching to Align Distributions for Test-Time-TrainingCode1
Language in a Bottle: Language Model Guided Concept Bottlenecks for Interpretable Image ClassificationCode1
Plug and Play Active Learning for Object DetectionCode1
Contrastive Losses Are Natural Criteria for Unsupervised Video SummarizationCode1
DeepVoxNet2: Yet another CNN frameworkCode1
Towards All-in-one Pre-training via Maximizing Multi-modal Mutual InformationCode1
FedFA: Federated Learning with Feature Anchors to Align Features and Classifiers for Heterogeneous DataCode1
Improving the Computer-Aided Estimation of Ulcerative Colitis Severity According to Mayo Endoscopic Score by Using Regression-Based Deep LearningCode1
Federated Adaptive Prompt Tuning for Multi-Domain Collaborative LearningCode1
Robust Deep Learning for Autonomous DrivingCode1
Fcaformer: Forward Cross Attention in Hybrid Vision TransformerCode1
PKCAM: Previous Knowledge Channel Attention ModuleCode1
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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