Featured Publications
Mutual Information Regularized Feature-Level Frankenstein for Discriminative Recognition.
Liu X, Yang C, You J, Kuo CJ, Kumar BVKV. Mutual Information Regularized Feature-Level Frankenstein for Discriminative Recognition. IEEE Trans Pattern Anal Mach Intell 2022, 44: 5243-5260. PMID: 33945470, DOI: 10.1109/TPAMI.2021.3077397.Peer-Reviewed Original ResearchOrdinal Unsupervised Domain Adaptation With Recursively Conditional Gaussian Imposed Variational Disentanglement.
Liu X, Li S, Ge Y, Ye P, You J, Lu J. Ordinal Unsupervised Domain Adaptation With Recursively Conditional Gaussian Imposed Variational Disentanglement. IEEE Trans Pattern Anal Mach Intell 2022, PP PMID: 35704544, DOI: 10.1109/TPAMI.2022.3183115.Peer-Reviewed Original ResearchSubtype-Aware Dynamic Unsupervised Domain Adaptation
Liu X, Xing F, You J, Lu J, Kuo C, Fakhri G, Woo J. Subtype-Aware Dynamic Unsupervised Domain Adaptation. IEEE Transactions On Neural Networks And Learning Systems 2024, 35: 2820-2834. PMID: 35895653, DOI: 10.1109/tnnls.2022.3192315.Peer-Reviewed Original ResearchTarget domainSource domain to target domainUnsupervised domain adaptationWithin-class compactnessHeart disease dataPseudo-labelsDomain adaptationClass centersLatent spaceCluster centroidsConditional alignmentLabel shiftTransfer knowledgeQueueing frameworkLocal proximityAlternative processing schemesSubtype labelsExperimental resultsProcessing schemeSubtype structureDomainNetVisDADisease dataDomainLabelingAttentive continuous generative self-training for unsupervised domain adaptive medical image translation
Liu X, Prince J, Xing F, Zhuo J, Reese T, Stone M, El Fakhri G, Woo J. Attentive continuous generative self-training for unsupervised domain adaptive medical image translation. Medical Image Analysis 2023, 88: 102851. PMID: 37329854, PMCID: PMC10527936, DOI: 10.1016/j.media.2023.102851.Peer-Reviewed Original ResearchConceptsUnsupervised domain adaptationImage translationProblem of domain shiftSelf-trainingImage modality translationLabeled source domainTarget domain dataSelf-attention schemeAlternating optimization schemeHeterogeneous target domainContinuous value predictionPseudo-labelsDomain adaptationUDA methodsDomain shiftSoftmax probabilitiesSource domainTarget domainVariational BayesBackground regionsTranslation tasksTraining processDomain dataGeneration taskOptimization schemeMemory consistent unsupervised off-the-shelf model adaptation for source-relaxed medical image segmentation
Liu X, Xing F, El Fakhri G, Woo J. Memory consistent unsupervised off-the-shelf model adaptation for source-relaxed medical image segmentation. Medical Image Analysis 2022, 83: 102641. PMID: 36265264, PMCID: PMC10016738, DOI: 10.1016/j.media.2022.102641.Peer-Reviewed Original ResearchConceptsUnsupervised domain adaptationUnsupervised domain adaptation methodsSource domain dataBN statisticsTarget domainLabeled source domain dataDomain dataLabeled source domainSelf-training strategyPatient data privacyHeterogeneous target domainBrain tumor segmentationPseudo-labelsDomain adaptationUnsupervised adaptationData privacySegmentation taskSource domainImage segmentationVital protocolAdaptation frameworkDecay strategyBoost performanceModel adaptationTumor segmentationAssessment of Transcatheter or Surgical Closure of Atrial Septal Defect using Interpretable Deep Keypoint Stadiometry.
Wang J, Xie W, Cheng M, Wu Q, Wang F, Li P, Fan B, Zhang X, Wang B, Liu X. Assessment of Transcatheter or Surgical Closure of Atrial Septal Defect using Interpretable Deep Keypoint Stadiometry. Research (Wash D C) 2022, 2022: 9790653. PMID: 36340508, DOI: 10.34133/2022/9790653.Peer-Reviewed Original ResearchVicinal Feature Statistics Augmentation for Federated 3D Medical Volume Segmentation
Huang Y, Xie W, Li M, Cheng M, Wu J, Wang W, You J, Liu X. Vicinal Feature Statistics Augmentation for Federated 3D Medical Volume Segmentation. InInternational Conference on Information Processing in Medical Imaging 2023 Jun 8 (pp. 360-371). Cham: Springer Nature Switzerland.Peer-Reviewed Original ResearchAUTO3D: Novel view synthesis through unsupervisely learned variational viewpoint and global 3D representation
Liu X, Che T, Lu Y, Yang C, Li S, You J. Auto3d: Novel view synthesis through unsupervisely learned variational viewpoint and global 3d representation. InEuropean Conference on Computer Vision 2020 Aug 23 (pp. 52-71). Cham: Springer International Publishing.Peer-Reviewed Original ResearchSeverity-aware semantic segmentation with reinforced wasserstein training
Liu X, Ji W, You J, Fakhri GE, Woo J. Severity-aware semantic segmentation with reinforced wasserstein training. InProceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition 2020 (pp. 12566-12575).Peer-Reviewed Original ResearchImportance-Aware Semantic Segmentation in Self-Driving with Discrete Wasserstein Training
Liu X, Han Y, Bai S, Ge Y, Wang T, Han X, Li S, You J, Lu J. Importance-aware semantic segmentation in self-driving with discrete wasserstein training. InProceedings of the AAAI Conference on Artificial Intelligence 2020 Apr 3 (Vol. 34, No. 07, pp. 11629-11636).Peer-Reviewed Original ResearchSeverity-Aware Semantic Segmentation with Reinforced Wasserstein Training
Liu X, Ji W, You J, Fakhri G, Woo J. Severity-Aware Semantic Segmentation with Reinforced Wasserstein Training. 2020, 00: 12563-12572. DOI: 10.1109/cvpr42600.2020.01258.Peer-Reviewed Original ResearchSemantic segmentationCARLA simulatorCross-entropyGround distance matrixWasserstein training frameworkAlternating optimization schemeCityscapes datasetDNN architecturesCE lossTraining frameworkSemantic classesGround metricInter-class correlationAutonomous vehiclesSuperior performanceOptimization schemeDNNCARLADistance matrixSurgery systemCamVidDeepLabSimulationCityscapesPixelSubtype-aware Unsupervised Domain Adaptation for Medical Diagnosis
Liu X, Liu X, Hu B, Ji W, Xing F, Lu J, You J, Kuo CC, El Fakhri G, Woo J. Subtype-aware unsupervised domain adaptation for medical diagnosis. In Proceedings of the AAAI Conference on Artificial Intelligence 2021 May 18 (Vol. 35, No. 3, pp. 2189-2197).Peer-Reviewed Original ResearchDeep Verifier Networks: Verification of Deep Discriminative Models with Deep Generative Models
Che T, Liu X, Li S, Ge Y, Zhang R, Xiong C, Bengio Y. Deep verifier networks: Verification of deep discriminative models with deep generative models. In Proceedings of the AAAI Conference on Artificial Intelligence 2021 May 18 (Vol. 35, No. 8, pp. 7002-7010).Peer-Reviewed Original ResearchAutomated interpretation of congenital heart disease from multi-view echocardiograms.
Wang J, Liu X, Wang F, Zheng L, Gao F, Zhang H, Zhang X, Xie W, Wang B. Automated interpretation of congenital heart disease from multi-view echocardiograms. Med Image Anal 2021, 69: 101942. PMID: 33418465, DOI: 10.1016/j.media.2020.101942.Peer-Reviewed Original ResearchDomain Generalization under Conditional and Label Shifts via Variational Bayesian Inference
Liu X, Hu B, Jin L, Han X, Xing F, Ouyang J, Lu J, El Fakhri G, Woo J. Domain Generalization under Conditional and Label Shifts via Variational Bayesian Inference. 2021, 881-887. DOI: 10.24963/ijcai.2021/122.Peer-Reviewed Original ResearchDomain generalizationDomain-invariant feature learningVariational Bayesian inference frameworkLabel shiftCross-domain accuracyLabeled source domainVariational Bayesian inferenceFeature learningBayesian inference frameworkLatent spaceSource domainTarget domainDistribution matchingTransfer knowledgeInference frameworkSuperior performanceP(x|yBayesian inferenceLabelingDomainFrameworkGeneralizationBenchmarksPosterior alignmentLearningAdversarial Unsupervised Domain Adaptation with Conditional and Label Shift: Infer, Align and Iterate
Liu X, Guo Z, Li S, Xing F, You J, Kuo C, Fakhri G, Woo J. Adversarial Unsupervised Domain Adaptation with Conditional and Label Shift: Infer, Align and Iterate. 2021, 00: 10347-10356. DOI: 10.1109/iccv48922.2021.01020.Peer-Reviewed Original ResearchUnsupervised domain adaptationDomain adaptationLabel shiftUnsupervised domain adaptation methodsAdversarial unsupervised domain adaptationAlternating optimization schemeUDA methodsTarget domainTraining stageOptimization schemeTesting stageExperimental resultsDistribution w.AdversaryP(x|yP(y|xDomainSchemeClassificationMethodInferenceAdaptationWasserstein loss with alternative reinforcement learning for severity-aware semantic segmentation
Liu X, Lu Y, Liu X, Bai S, Li S, You J. Wasserstein loss with alternative reinforcement learning for severity-aware semantic segmentation. IEEE Transactions on Intelligent Transportation Systems. 2020 Sep 10;23(1):587-96.Peer-Reviewed Original ResearchPermutation-invariant Feature Restructuring for Correlation-aware Image Set-based Recognition
Liu X, Guo Z, Li S, Kong L, Jia P, You J, Kumar BV. Permutation-invariant feature restructuring for correlation-aware image set-based recognition. InProceedings of the IEEE/CVF International Conference on Computer Vision 2019 (pp. 4986-4996).Peer-Reviewed Original ResearchConfidence Regularized Self-Training
Zou Y, Yu Z, Liu X, Kumar BV, Wang J. Confidence regularized self-training. In Proceedings of the IEEE/CVF International Conference on Computer Vision 2019 (pp. 5982-5991).Peer-Reviewed Original ResearchDependency-aware Attention Control for Unconstrained Face Recognition with Image Sets
Liu X, Kumar BV, Yang C, Tang Q, You J. Dependency-aware attention control for unconstrained face recognition with image sets. In Proceedings of the European Conference on Computer Vision (ECCV) 2018 (pp. 548-565).Peer-Reviewed Original Research