{"about":{"non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","site":"https://codewithpapers.app","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page","syntology":{"site":"https://syntology.ai","developers":"https://syntology.ai/developers","mcp":{"server":"https://syntology.ai/mcp","transport":"streamable-http","server_card":"https://syntology.ai/.well-known/mcp/server-card.json","auth":{"type":"trial token, no account","trial_token":"https://syntology.ai/api/oauth/trial/token","method":"POST","docs":"https://syntology.ai/developers"}},"have":"https://syntology.ai/api/graph/have?x=<method, arXiv id or title> (free, answers coverage only)","paper_base":"https://syntology.ai/paper/","atlas_base":"https://app.syntology.ai/?focus="},"machine_readable":[{"url":"https://codewithpapers.app/llms.txt","what":"the machine catalog: every machine-readable file, counted"},{"url":"https://codewithpapers.app/index/manifest.json","what":"paper-to-code index by arXiv id, with Syntology's counts"},{"url":"https://codewithpapers.app/search/manifest.json","what":"site search index (titles, authors) and its files"},{"url":"https://codewithpapers.app/download","what":"bulk files: Syntology's layer, described there"},{"url":"https://codewithpapers.app/build_manifest.json","what":"the build record: inputs, counts, exclusions, probes"}]},"url":"/task/unsupervised-domain-adaptation/papers/18","list_of":"/task/unsupervised-domain-adaptation","task":"Unsupervised Domain Adaptation","archive":{"snapshot":"2025-07-28"},"key_notes":{"n_ran_checked":"legacy name, kept unchanged so existing readers do not break: it counts the samples that ran with no instrument failure (honoured, violated, and ran with no contract checked); it does not mean a contract was checked, and the pages print it as 'K with no instrument failure', not 'K checked'","n_constructed":"a sub-count of the samples that ran, never subtracted from them and never a failure: an executed sample whose run returned an instance of its own class (fixture_out_type equals the entry name): the run built an object and did not compute a result (Syntology's RAN record, counts.constructed)"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"repositories listed in the archive (most first), then date (newest first), then slug","page":18,"pages_in_order":20,"rows_per_page":100,"rows":[1701,1800],"of":1951,"counts":{"archive_papers_tagged":1951,"with_a_code_link":864,"where_syntology_ran_a_sample":200,"not_listed_spam_title":0,"listed":1951,"listed_where_code_ran":200,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":177,"every_run_a_failure_of_syntologys_instrument":23,"listed_with_a_run_with_no_instrument_failure":177,"listed_every_run_a_failure_of_syntologys_instrument":23,"filter":{"states":["a run with no instrument failure","any run, instrument failures included"],"default":"a run with no instrument failure","note":"on the 'only where code ran' pages the default hides, in the browser, the rows where every run was a failure of Syntology's instrument; the second state shows them again. Rows are hidden, never re-ordered; these twins list every row"}},"definition":"distinct papers the archive tags; 'where Syntology ran a sample' counts papers with at least one harvested sample that ran, which is not a correctness claim"},"first_page":"/task/unsupervised-domain-adaptation","prev":"/task/unsupervised-domain-adaptation/papers/17","next":"/task/unsupervised-domain-adaptation/papers/19","papers":[{"url":null,"slug":"domain-adaptive-multibranch-networks","title":"Domain Adaptive Multibranch Networks","date":"2020-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"unsupervised-domain-adaptation-for-acoustic","title":"Unsupervised Domain Adaptation for Acoustic Scene Classification Using Band-Wise Statistics Matching","date":"2020-04-30","arxiv_id":"2005.00145","repositories_listed":0,"syntology":null},{"url":null,"slug":"unsupervised-domain-adaptation-with-multiple","title":"Unsupervised Domain Adaptation with Multiple Domain Discriminators and Adaptive Self-Training","date":"2020-04-27","arxiv_id":"2004.12724","repositories_listed":0,"syntology":null},{"url":null,"slug":"what-can-be-transferred-unsupervised-domain","title":"What Can Be Transferred: Unsupervised Domain Adaptation for Endoscopic Lesions Segmentation","date":"2020-04-24","arxiv_id":"2004.11500","repositories_listed":0,"syntology":null},{"url":null,"slug":"metric-learning-assisted-domain-adaptation","title":"Metric-Learning-Assisted Domain Adaptation","date":"2020-04-23","arxiv_id":"2004.10963","repositories_listed":0,"syntology":null},{"url":null,"slug":"class-distribution-alignment-for-adversarial","title":"Class Distribution Alignment for Adversarial Domain Adaptation","date":"2020-04-20","arxiv_id":"2004.09403","repositories_listed":0,"syntology":null},{"url":"/paper/unsupervised-person-re-identification-via-1","slug":"unsupervised-person-re-identification-via-1","title":"Unsupervised Person Re-identification via Multi-label Classification","date":"2020-04-20","arxiv_id":"2004.09228","repositories_listed":0,"syntology":null},{"url":"/paper/ad-cluster-augmented-discriminative","slug":"ad-cluster-augmented-discriminative","title":"AD-Cluster: Augmented Discriminative Clustering for Domain Adaptive Person Re-identification","date":"2020-04-19","arxiv_id":"2004.08787","repositories_listed":0,"syntology":null},{"url":null,"slug":"uncertainty-aware-consistency-regularization","title":"Uncertainty-Aware Consistency Regularization for Cross-Domain Semantic Segmentation","date":"2020-04-19","arxiv_id":"2004.08878","repositories_listed":0,"syntology":null},{"url":null,"slug":"online-meta-learning-for-multi-source-and","title":"Online Meta-Learning for Multi-Source and Semi-Supervised Domain Adaptation","date":"2020-04-09","arxiv_id":"2004.04398","repositories_listed":0,"syntology":null},{"url":null,"slug":"training-neural-networks-to-produce","title":"Towards Reusable Network Components by Learning Compatible Representations","date":"2020-04-08","arxiv_id":"2004.03898","repositories_listed":0,"syntology":null},{"url":null,"slug":"unsupervised-domain-adaptation-with-5","title":"Unsupervised Domain Adaptation with Progressive Domain Augmentation","date":"2020-04-03","arxiv_id":"2004.01735","repositories_listed":0,"syntology":null},{"url":null,"slug":"buda-boundless-unsupervised-domain-adaptation","title":"Handling new target classes in semantic segmentation with domain adaptation","date":"2020-04-02","arxiv_id":"2004.01130","repositories_listed":0,"syntology":null},{"url":null,"slug":"panda-prototypical-unsupervised-domain","title":"Semantic Domain Adversarial Networks for Unsupervised Domain Adaptation","date":"2020-03-30","arxiv_id":"2003.13274","repositories_listed":0,"syntology":null},{"url":"/paper/adaptive-object-detection-with-dual-multi","slug":"adaptive-object-detection-with-dual-multi","title":"Adaptive Object Detection with Dual Multi-Label Prediction","date":"2020-03-29","arxiv_id":"2003.12943","repositories_listed":0,"syntology":null},{"url":null,"slug":"mutual-learning-network-for-multi-source","title":"Mutual Learning Network for Multi-Source Domain Adaptation","date":"2020-03-29","arxiv_id":"2003.12944","repositories_listed":0,"syntology":null},{"url":"/paper/spatial-attention-pyramid-network-for","slug":"spatial-attention-pyramid-network-for","title":"Spatial Attention Pyramid Network for Unsupervised Domain Adaptation","date":"2020-03-29","arxiv_id":"2003.12979","repositories_listed":0,"syntology":null},{"url":null,"slug":"unsupervised-domain-adaptation-with-exploring","title":"Learning transferable and discriminative features for unsupervised domain adaptation","date":"2020-03-26","arxiv_id":"2003.11723","repositories_listed":0,"syntology":null},{"url":null,"slug":"self-guided-adaptation-progressive","title":"Self-Guided Adaptation: Progressive Representation Alignment for Domain Adaptive Object Detection","date":"2020-03-19","arxiv_id":"2003.08777","repositories_listed":0,"syntology":null},{"url":null,"slug":"cross-domain-self-supervised-learning-for","title":"Cross-domain Self-supervised Learning for Domain Adaptation with Few Source Labels","date":"2020-03-18","arxiv_id":"2003.08264","repositories_listed":0,"syntology":null},{"url":null,"slug":"domain-adaptation-through-transferring-both","title":"Unsupervised Domain Adaptation Through Transferring both the Source-Knowledge and Target-Relatedness Simultaneously","date":"2020-03-18","arxiv_id":"2003.08051","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-label-proportions-estimation-technique-for","title":"A Label Proportions Estimation Technique for Adversarial Domain Adaptation in Text Classification","date":"2020-03-16","arxiv_id":"2003.07444","repositories_listed":0,"syntology":null},{"url":"/paper/adapting-object-detectors-with-conditional","slug":"adapting-object-detectors-with-conditional","title":"Adapting Object Detectors with Conditional Domain Normalization","date":"2020-03-16","arxiv_id":"2003.07071","repositories_listed":0,"syntology":null},{"url":null,"slug":"semantic-segmentation-of-highly-class","title":"Semantic Segmentation of highly class imbalanced fully labelled 3D volumetric biomedical images and unsupervised Domain Adaptation of the pre-trained Segmentation Network to segment another fully unlabelled Biomedical 3D Image stack","date":"2020-03-13","arxiv_id":"2004.02748","repositories_listed":0,"syntology":null},{"url":"/paper/label-driven-reconstruction-for-domain","slug":"label-driven-reconstruction-for-domain","title":"Label-Driven Reconstruction for Domain Adaptation in Semantic Segmentation","date":"2020-03-10","arxiv_id":"2003.04614","repositories_listed":0,"syntology":null},{"url":"/paper/context-aware-domain-adaptation-in-semantic","slug":"context-aware-domain-adaptation-in-semantic","title":"Context-Aware Domain Adaptation in Semantic Segmentation","date":"2020-03-09","arxiv_id":"2003.04010","repositories_listed":0,"syntology":null},{"url":null,"slug":"unsupervised-adversarial-domain-adaptation-3","title":"Unsupervised Adversarial Domain Adaptation for Implicit Discourse Relation Classification","date":"2020-03-04","arxiv_id":"2003.02244","repositories_listed":0,"syntology":null},{"url":null,"slug":"unsupervised-domain-adaptation-for-mammogram","title":"Unsupervised Domain Adaptation for Mammogram Image Classification: A Promising Tool for Model Generalization","date":"2020-03-02","arxiv_id":"2003.01111","repositories_listed":0,"syntology":null},{"url":null,"slug":"calibrated-prediction-with-covariate-shift","title":"Calibrated Prediction with Covariate Shift via Unsupervised Domain Adaptation","date":"2020-02-29","arxiv_id":"2003.00343","repositories_listed":0,"syntology":null},{"url":null,"slug":"domain-decluttering-simplifying-images-to","title":"Domain Decluttering: Simplifying Images to Mitigate Synthetic-Real Domain Shift and Improve Depth Estimation","date":"2020-02-27","arxiv_id":"2002.12114","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-step-online-unsupervised-domain","title":"Multi-step Online Unsupervised Domain Adaptation","date":"2020-02-20","arxiv_id":"2002.08930","repositories_listed":0,"syntology":null},{"url":null,"slug":"unsupervised-domain-adaptation-via-3","title":"Unsupervised Domain Adaptation via Discriminative Manifold Embedding and Alignment","date":"2020-02-20","arxiv_id":"2002.08675","repositories_listed":0,"syntology":null},{"url":null,"slug":"enlarging-discriminative-power-by-adding-an","title":"Enlarging Discriminative Power by Adding an Extra Class in Unsupervised Domain Adaptation","date":"2020-02-19","arxiv_id":"2002.08041","repositories_listed":0,"syntology":null},{"url":null,"slug":"bi-directional-generation-for-unsupervised","title":"Bi-Directional Generation for Unsupervised Domain Adaptation","date":"2020-02-12","arxiv_id":"2002.04869","repositories_listed":0,"syntology":null},{"url":null,"slug":"dual-triplet-metric-learning-for-unsupervised","title":"Dual-Triplet Metric Learning for Unsupervised Domain Adaptation in Video-Based Face Recognition","date":"2020-02-11","arxiv_id":"2002.04206","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-numerical-observers-using","title":"Learning Numerical Observers using Unsupervised Domain Adaptation","date":"2020-02-03","arxiv_id":"2002.03763","repositories_listed":0,"syntology":null},{"url":null,"slug":"single-stage-object-detection-from-top-view","title":"Single-Stage Object Detection from Top-View Grid Maps on Custom Sensor Setups","date":"2020-02-03","arxiv_id":"2002.00667","repositories_listed":0,"syntology":null},{"url":null,"slug":"unsupervised-domain-adaptive-object-detection","title":"Unsupervised Domain Adaptive Object Detection using Forward-Backward Cyclic Adaptation","date":"2020-02-03","arxiv_id":"2002.00575","repositories_listed":0,"syntology":null},{"url":null,"slug":"adversarial-domain-adaptation-for-cell","title":"Adversarial Domain Adaptation for Cell Segmentation","date":"2020-01-29","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"e-uda-efficient-unsupervised-domain","title":"Domain Adaptive Medical Image Segmentation via Adversarial Learning of Disease-Specific Spatial Patterns","date":"2020-01-25","arxiv_id":"2001.09313","repositories_listed":0,"syntology":null},{"url":null,"slug":"unsupervised-learning-of-multimodal-image-1","title":"Unsupervised learning of multimodal image registration using domain adaptation with projected Earth Mover’s discrepancies","date":"2020-01-25","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"generalization-bounds-and-representation","title":"Generalization Bounds and Representation Learning for Estimation of Potential Outcomes and Causal Effects","date":"2020-01-21","arxiv_id":"2001.07426","repositories_listed":0,"syntology":null},{"url":null,"slug":"unsupervised-domain-adaptation-for-mobile","title":"Unsupervised Domain Adaptation for Mobile Semantic Segmentation based on Cycle Consistency and Feature Alignment","date":"2020-01-14","arxiv_id":"2001.04692","repositories_listed":0,"syntology":null},{"url":null,"slug":"unsupervised-domain-adaptation-in-person-re","title":"Unsupervised Domain Adaptation in Person re-ID via k-Reciprocal Clustering and Large-Scale Heterogeneous Environment Synthesis","date":"2020-01-14","arxiv_id":"2001.04928","repositories_listed":0,"syntology":null},{"url":"/paper/multi-source-domain-adaptation-for-text","slug":"multi-source-domain-adaptation-for-text","title":"Multi-Source Domain Adaptation for Text Classification via DistanceNet-Bandits","date":"2020-01-13","arxiv_id":"2001.04362","repositories_listed":0,"syntology":null},{"url":null,"slug":"crdoco-pixel-level-domain-transfer-with-cross-1","title":"CrDoCo: Pixel-level Domain Transfer with Cross-Domain Consistency","date":"2020-01-09","arxiv_id":"2001.03182","repositories_listed":0,"syntology":null},{"url":null,"slug":"domain-adaptation-via-teacher-student","title":"Domain Adaptation via Teacher-Student Learning for End-to-End Speech Recognition","date":"2020-01-06","arxiv_id":"2001.01798","repositories_listed":0,"syntology":null},{"url":null,"slug":"low-budget-unsupervised-label-query-through","title":"Low-Budget Label Query through Domain Alignment Enforcement","date":"2020-01-01","arxiv_id":"2001.00238","repositories_listed":0,"syntology":null},{"url":null,"slug":"understanding-and-estimating-the-adaptability","title":"Understanding and Estimating the Adaptability of Domain-Invariant Representations","date":"2020-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"characteristic-regularisation-for-super","title":"Characteristic Regularisation for Super-Resolving Face Images","date":"2019-12-30","arxiv_id":"1912.12987","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-adversarial-perturbation-oriented-domain","title":"An Adversarial Perturbation Oriented Domain Adaptation Approach for Semantic Segmentation","date":"2019-12-18","arxiv_id":"1912.08954","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-domain-adaptive-features-with","title":"Learning Domain Adaptive Features with Unlabeled Domain Bridges","date":"2019-12-10","arxiv_id":"1912.05004","repositories_listed":0,"syntology":null},{"url":null,"slug":"class-conditional-domain-adaptation-on","title":"Class-Conditional Domain Adaptation on Semantic Segmentation","date":"2019-11-27","arxiv_id":"1911.11981","repositories_listed":0,"syntology":null},{"url":null,"slug":"spatial-aware-gan-for-unsupervised-person-re","title":"Spatial-Aware GAN for Unsupervised Person Re-identification","date":"2019-11-26","arxiv_id":"1911.11312","repositories_listed":0,"syntology":null},{"url":null,"slug":"unsupervised-domain-adaptation-of-language","title":"Unsupervised Domain Adaptation of Language Models for Reading Comprehension","date":"2019-11-25","arxiv_id":"1911.10768","repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-unsupervised-domain-adaptation-with","title":"Improving Unsupervised Domain Adaptation with Variational Information Bottleneck","date":"2019-11-21","arxiv_id":"1911.09310","repositories_listed":0,"syntology":null},{"url":null,"slug":"unsupervised-domain-adaptation-by-optical","title":"Unsupervised Domain Adaptation by Optical Flow Augmentation in Semantic Segmentation","date":"2019-11-20","arxiv_id":"1911.09652","repositories_listed":0,"syntology":null},{"url":null,"slug":"copy-move-forgery-classification-via","title":"Copy-Move Forgery Classification via Unsupervised Domain Adaptation","date":"2019-11-14","arxiv_id":"1911.07932","repositories_listed":0,"syntology":null},{"url":null,"slug":"unsupervised-domain-adaptation-of-contextual","title":"Unsupervised Domain Adaptation of Contextual Embeddings for Low-Resource Duplicate Question Detection","date":"2019-11-06","arxiv_id":"1911.02645","repositories_listed":0,"syntology":null},{"url":null,"slug":"air-writing-translater-a-novel-unsupervised","title":"Air-Writing Translater: A Novel Unsupervised Domain Adaptation Method for Inertia-Trajectory Translation of In-air Handwriting","date":"2019-11-01","arxiv_id":"1911.05649","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-causal-representation-learning-for","title":"Deep causal representation learning for unsupervised domain adaptation","date":"2019-10-28","arxiv_id":"1910.12417","repositories_listed":0,"syntology":null},{"url":null,"slug":"hierarchical-clustering-guided-re-id-with","title":"Hierarchical Clustering with Hard-batch Triplet Loss for Person Re-identification","date":"2019-10-27","arxiv_id":"1910.12278","repositories_listed":0,"syntology":null},{"url":null,"slug":"domain-bridge-for-unpaired-image-to-image","title":"Domain Bridge for Unpaired Image-to-Image Translation and Unsupervised Domain Adaptation","date":"2019-10-23","arxiv_id":"1910.10563","repositories_listed":0,"syntology":null},{"url":null,"slug":"generalized-domain-adaptation-with-covariate-1","title":"Class-imbalanced Domain Adaptation: An Empirical Odyssey","date":"2019-10-23","arxiv_id":"1910.10320","repositories_listed":0,"syntology":null},{"url":null,"slug":"generative-adversarial-networks-and-domain","title":"Generative Adversarial Networks And Domain Adaptation For Training Data Independent Image Registration","date":"2019-10-18","arxiv_id":"1910.08593","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-general-upper-bound-for-unsupervised-domain","title":"A General Upper Bound for Unsupervised Domain Adaptation","date":"2019-10-03","arxiv_id":"1910.01409","repositories_listed":0,"syntology":null},{"url":"/paper/instance-guided-context-rendering-for-cross","slug":"instance-guided-context-rendering-for-cross","title":"Instance-Guided Context Rendering for Cross-Domain Person Re-Identification","date":"2019-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"racial-faces-in-the-wild-reducing-racial-bias-1","title":"Racial Faces in the Wild: Reducing Racial Bias by Information Maximization Adaptation Network","date":"2019-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"self-adaptive-soft-voice-activity-detection","title":"Self-Adaptive Soft Voice Activity Detection using Deep Neural Networks for Robust Speaker Verification","date":"2019-09-26","arxiv_id":"1909.11886","repositories_listed":0,"syntology":null},{"url":null,"slug":"task-discriminative-domain-alignment-for","title":"Task-Discriminative Domain Alignment for Unsupervised Domain Adaptation","date":"2019-09-26","arxiv_id":"1909.12366","repositories_listed":0,"syntology":null},{"url":null,"slug":"distribution-matching-prototypical-network","title":"Distribution Matching Prototypical Network for Unsupervised Domain Adaptation","date":"2019-09-25","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-step-decentralized-domain-adaptation","title":"Multi-Step Decentralized Domain Adaptation","date":"2019-09-25","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"prototype-assisted-adversarial-learning-for","title":"PROTOTYPE-ASSISTED ADVERSARIAL LEARNING FOR UNSUPERVISED DOMAIN ADAPTATION","date":"2019-09-25","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"transfer-alignment-network-for-double-blind","title":"Transfer Alignment Network for Double Blind Unsupervised Domain Adaptation","date":"2019-09-25","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"unsupervised-domain-adaptation-with-7","title":"Unsupervised domain adaptation with imputation","date":"2019-09-25","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"wildly-unsupervised-domain-adaptation-and-its","title":"Wildly Unsupervised Domain Adaptation and Its Powerful and Efficient Solution","date":"2019-09-25","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"restyling-data-application-to-unsupervised","title":"Restyling Data: Application to Unsupervised Domain Adaptation","date":"2019-09-24","arxiv_id":"1909.10900","repositories_listed":0,"syntology":null},{"url":"/paper/190909675","slug":"190909675","title":"Cross-Dataset Person Re-Identification via Unsupervised Pose Disentanglement and Adaptation","date":"2019-09-20","arxiv_id":"1909.09675","repositories_listed":0,"syntology":null},{"url":null,"slug":"wasserstein-distance-based-domain-adaptation","title":"Wasserstein Distance Based Domain Adaptation for Object Detection","date":"2019-09-18","arxiv_id":"1909.08675","repositories_listed":0,"syntology":null},{"url":null,"slug":"using-latent-codes-for-class-imbalance","title":"Using Latent Codes for Class Imbalance Problem in Unsupervised Domain Adaptation","date":"2019-09-17","arxiv_id":"1909.08962","repositories_listed":0,"syntology":null},{"url":null,"slug":"contrastively-smoothed-class-alignment-for","title":"Contrastively Smoothed Class Alignment for Unsupervised Domain Adaptation","date":"2019-09-11","arxiv_id":"1909.05288","repositories_listed":0,"syntology":null},{"url":null,"slug":"adversarial-learning-and-self-teaching","title":"Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation","date":"2019-09-02","arxiv_id":"1909.00781","repositories_listed":0,"syntology":null},{"url":null,"slug":"estimation-of-absolute-scale-in-monocular","title":"Estimation of Absolute Scale in Monocular SLAM Using Synthetic Data","date":"2019-09-02","arxiv_id":"1909.00713","repositories_listed":0,"syntology":null},{"url":null,"slug":"self-ensembling-with-gan-based-data","title":"Self-Ensembling with GAN-based Data Augmentation for Domain Adaptation in Semantic Segmentation","date":"2019-09-02","arxiv_id":"1909.00589","repositories_listed":0,"syntology":null},{"url":null,"slug":"self-training-and-adversarial-background","title":"Self-Training and Adversarial Background Regularization for Unsupervised Domain Adaptive One-Stage Object Detection","date":"2019-09-02","arxiv_id":"1909.00597","repositories_listed":0,"syntology":null},{"url":null,"slug":"self-adaptation-for-unsupervised-domain","title":"Self-Adaptation for Unsupervised Domain Adaptation","date":"2019-09-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"adversarial-domain-adaptation-for-machine","title":"Adversarial Domain Adaptation for Machine Reading Comprehension","date":"2019-08-24","arxiv_id":"1908.09209","repositories_listed":0,"syntology":null},{"url":null,"slug":"190807926","title":"TUNA-Net: Task-oriented UNsupervised Adversarial Network for Disease Recognition in Cross-Domain Chest X-rays","date":"2019-08-21","arxiv_id":"1908.07926","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-vision-based-flight-in-drone-swarms","title":"Learning Vision-based Flight in Drone Swarms by Imitation","date":"2019-08-08","arxiv_id":"1908.02999","repositories_listed":0,"syntology":null},{"url":"/paper/learning-to-adapt-invariance-in-memory-for","slug":"learning-to-adapt-invariance-in-memory-for","title":"Learning to Adapt Invariance in Memory for Person Re-identification","date":"2019-08-01","arxiv_id":"1908.00485","repositories_listed":0,"syntology":null},{"url":null,"slug":"pseudo-labeling-curriculum-for-unsupervised","title":"Pseudo-Labeling Curriculum for Unsupervised Domain Adaptation","date":"2019-08-01","arxiv_id":"1908.00262","repositories_listed":0,"syntology":null},{"url":null,"slug":"unsupervised-domain-adaptation-via-1","title":"Unsupervised Domain Adaptation via Disentangled Representations: Application to Cross-Modality Liver Segmentation","date":"2019-07-31","arxiv_id":"1907.13590","repositories_listed":0,"syntology":null},{"url":null,"slug":"hidden-covariate-shift-a-minimal-assumption","title":"Hidden Covariate Shift: A Minimal Assumption For Domain Adaptation","date":"2019-07-29","arxiv_id":"1907.12299","repositories_listed":0,"syntology":null},{"url":null,"slug":"universal-person-re-identification","title":"Universal Person Re-Identification","date":"2019-07-22","arxiv_id":"1907.09511","repositories_listed":0,"syntology":null},{"url":"/paper/learning-to-optimize-domain-specific","slug":"learning-to-optimize-domain-specific","title":"Learning to Optimize Domain Specific Normalization for Domain Generalization","date":"2019-07-09","arxiv_id":"1907.04275","repositories_listed":0,"syntology":null},{"url":null,"slug":"data-efficient-unsupervised-domain-adaptation","title":"Data Efficient Unsupervised Domain Adaptation for Cross-Modality Image Segmentation","date":"2019-07-05","arxiv_id":"1907.02766","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-a-domain-invariant-embedding-for","title":"Learning a Domain-Invariant Embedding for Unsupervised Domain Adaptation Using Class-Conditioned Distribution Alignment","date":"2019-07-04","arxiv_id":"1907.02271","repositories_listed":0,"syntology":null},{"url":null,"slug":"bayesian-uncertainty-matching-for","title":"Bayesian Uncertainty Matching for Unsupervised Domain Adaptation","date":"2019-06-24","arxiv_id":"1906.09693","repositories_listed":0,"syntology":null},{"url":null,"slug":"decomposable-neural-paraphrase-generation","title":"Decomposable Neural Paraphrase Generation","date":"2019-06-24","arxiv_id":"1906.09741","repositories_listed":0,"syntology":null},{"url":null,"slug":"transferrable-operative-difficulty-assessment","title":"Transferrable Operative Difficulty Assessment in Robot-assisted Teleoperation: A Domain Adaptation Approach","date":"2019-06-12","arxiv_id":"1906.04934","repositories_listed":0,"syntology":null}],"record_sha256":"5b805782434528a069b11274654f4730a1b8ae4b3872893704b9a581d4f9c9b6","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}