mlsanityData to 7 Oct 2026

Domain adaptation, Explainability & Fairness in AI for Medical Image Analysis: Diagnosis of COVID-19 based on 3-D Chest CT-scans

arXiv 2403.02192 ↗First posted 4 Mar 2024eess.IV cs.CVcited by 30

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Abstract (arXiv)

The paper presents the DEF-AI-MIA COV19D Competition, which is organized in the framework of the 'Domain adaptation, Explainability, Fairness in AI for Medical Image Analysis (DEF-AI-MIA)' Workshop of the 2024 Computer Vision and Pattern Recognition (CVPR) Conference. The Competition is the 4th in the series, following the first three Competitions held in the framework of ICCV 2021, ECCV 2022 and ICASSP 2023 International Conferences respectively. It includes two Challenges on: i) Covid-19 Detection and ii) Covid-19 Domain Adaptation. The Competition use data from COV19-CT-DB database, which is described in the paper and includes a large number of chest CT scan series. Each chest CT scan series consists of a sequence of 2-D CT slices, the number of which is between 50 and 700. Training, validation and test datasets have been extracted from COV19-CT-DB and provided to the participants in both Challenges. The paper presents the baseline models used in the Challenges and the performance which was obtained respectively.

Key facts. Cited by 30 papers in the map (data through 7 Oct 2026). Builds on 20 of its 58 references that are in the map. First posted on arXiv 4 Mar 2024.

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20 of 58 references.

References · 20

  1. 2019Expression, Affect, Action Unit Recognition: Aff-Wild2, Multi-Task Learning and ArcFacecited by 222
  2. 2020Analysing Affective Behavior in the First ABAW 2020 Competitioncited by 178
  3. 2021Affect Analysis in-the-wild: Valence-Arousal, Expressions, Action Units and a Unified Frameworkcited by 174
  4. 2021Distribution Matching for Heterogeneous Multi-Task Learning: a Large-scale Face Studycited by 168
  5. 2021Analysing Affective Behavior in the second ABAW2 Competitioncited by 163
  6. 2022ABAW: Valence-Arousal Estimation, Expression Recognition, Action Unit Detection & Multi-Task Learning Challengescited by 156
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  10. 2024The 6th Affective Behavior Analysis in-the-wild (ABAW) Competitioncited by 78
  11. 2020Deep Transparent Prediction through Latent Representation Analysiscited by 72
  12. 2021MIA-COV19D: COVID-19 Detection through 3-D Chest CT Image Analysiscited by 72
8 more
  1. 2024Distribution Matching for Multi-Task Learning of Classification Tasks: a Large-Scale Study on Faces & Beyondcited by 60
  2. 2019Exploiting multi-CNN features in CNN-RNN based Dimensional Emotion Recognition on the OMG in-the-wild Datasetcited by 39
  3. 2023A Deep Neural Architecture for Harmonizing 3-D Input Data Analysis and Decision Making in Medical Imagingcited by 39
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Citing papers per year: 2024: 17; 2025: 7; 2026: 6.

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  1. 20247th ABAW Competition: Multi-Task Learning and Compound Expression Recognitioncited by 53
  2. 2024COVID-19 Computer-aided Diagnosis through AI-assisted CT Imaging Analysis: Deploying a Medical AI Systemcited by 23
  3. 2024Behaviour4All: in-the-wild Facial Behaviour Analysis Toolkitcited by 16
  4. 2024SAM2CLIP2SAM: Vision Language Model for Segmentation of 3D CT Scans for Covid-19 Detectioncited by 14
  5. 2025DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarioscited by 13
  6. 2024Robust COVID-19 Detection in CT Images with CLIPcited by 12
  7. 2024Can Machine Learning Assist in Diagnosis of Primary Immune Thrombocytopenia? A feasibility studycited by 8
  8. 2024Using Prompts to Guide Large Language Models in Imitating a Real Person's Language Stylecited by 6
  9. 2025Preserving AUC Fairness in Learning with Noisy Protected Groupscited by 6
  10. 2024Advancing COVID-19 Detection in 3D CT Scanscited by 5
  11. 2025Multi-Source COVID-19 Detection via Variance Risk Extrapolationcited by 5
  12. 2024Robust Facial Reactions Generation: An Emotion-Aware Framework with Modality Compensationcited by 4
18 more
  1. 2025Advancing Lung Disease Diagnosis in 3D CT Scanscited by 4
  2. 2024Domain Adaptation Using Pseudo Labels for COVID-19 Detectioncited by 3
  3. 2024A Closer Look at Spatial-Slice Features Learning for COVID-19 Detectioncited by 3
  4. 2024Simple 2D Convolutional Neural Network-based Approach for COVID-19 Detectioncited by 2
  5. 2025Taming Domain Shift in Multi-source CT-Scan Classification via Input-Space Standardizationcited by 2
  6. 2025Multi Source COVID-19 Detection via Kernel-Density-based Slice Samplingcited by 1
  7. 2024Ensembling and Test Augmentation for Covid-19 Detection and Covid-19 Domain Adaptation from 3D CT-Scanscited by 0
  8. 2024COVID-19 detection from pulmonary CT scans using a novel EfficientNet with attention mechanismcited by 0
  9. 2024High-confidence pseudo-labels for domain adaptation in COVID-19 detectioncited by 0
  10. 2024Multi-Task Learning for Affect Analysiscited by 0
  11. 2024Emotion Detection through Body Gesture and Facecited by 0
  12. 2025Stable-Drift: A Patient-Aware Latent Drift Replay Method for Stabilizing Representations in Continual Learningcited by 0
  13. 2026Domain Generalization for Time Series: Enhancing Drilling Regression Models for Stick-Slip Index Predictioncited by 0
  14. 2026A Heterogeneous Ensemble for Multi-Center COVID-19 Classification from Chest CT Scanscited by 0
  15. 2026Clinical Priors Guided Lung Disease Detection in 3D CT Scanscited by 0
  16. 2026Vision-Language Model Based Multi-Expert Fusion for CT Image Classificationcited by 0
  17. 2026Robust Multi-Source Covid-19 Detection in CT Imagescited by 0
  18. 2026Robust Fair Disease Diagnosis in CT Imagescited by 0