{"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/image-to-image-translation/papers/5","list_of":"/task/image-to-image-translation","task":"Image-to-Image Translation","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":5,"pages_in_order":12,"rows_per_page":100,"rows":[401,500],"of":1184,"counts":{"archive_papers_tagged":1184,"with_a_code_link":550,"where_syntology_ran_a_sample":126,"not_listed_spam_title":0,"listed":1184,"listed_where_code_ran":126,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":108,"every_run_a_failure_of_syntologys_instrument":18,"listed_with_a_run_with_no_instrument_failure":108,"listed_every_run_a_failure_of_syntologys_instrument":18,"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/image-to-image-translation","prev":"/task/image-to-image-translation/papers/4","next":"/task/image-to-image-translation/papers/6","papers":[{"url":"/paper/frequency-domain-image-translation-more-photo","slug":"frequency-domain-image-translation-more-photo","title":"Frequency Domain Image Translation: More Photo-realistic, Better Identity-preserving","date":"2020-11-27","arxiv_id":"2011.13611","repositories_listed":1,"syntology":null},{"url":"/paper/how-to-train-your-conditional-gan-an-approach","slug":"how-to-train-your-conditional-gan-an-approach","title":"Rethinking conditional GAN training: An approach using geometrically structured latent manifolds","date":"2020-11-25","arxiv_id":"2011.13055","repositories_listed":1,"syntology":null},{"url":"/paper/deepi2i-enabling-deep-hierarchical-image-to","slug":"deepi2i-enabling-deep-hierarchical-image-to","title":"DeepI2I: Enabling Deep Hierarchical Image-to-Image Translation by Transferring from GANs","date":"2020-11-11","arxiv_id":"2011.05867","repositories_listed":1,"syntology":null},{"url":"/paper/zero-pair-image-to-image-translation-using","slug":"zero-pair-image-to-image-translation-using","title":"Zero-Pair Image to Image Translation using Domain Conditional Normalization","date":"2020-11-11","arxiv_id":"2011.05680","repositories_listed":1,"syntology":null},{"url":"/paper/deep-multimodal-fusion-by-channel-exchanging","slug":"deep-multimodal-fusion-by-channel-exchanging","title":"Deep Multimodal Fusion by Channel Exchanging","date":"2020-11-10","arxiv_id":"2011.05005","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/deep-multimodal-fusion-by-channel-exchanging#ran","syntology_url":"https://syntology.ai/paper/2011.05005","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2011.05005"}},"official":{"repos":["yikaiw/CEN"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/bggan-bokeh-glass-generative-adversarial","slug":"bggan-bokeh-glass-generative-adversarial","title":"BGGAN: Bokeh-Glass Generative Adversarial Network for Rendering Realistic Bokeh","date":"2020-11-04","arxiv_id":"2011.02242","repositories_listed":1,"syntology":null},{"url":"/paper/continuous-and-diverse-image-to-image","slug":"continuous-and-diverse-image-to-image","title":"Continuous and Diverse Image-to-Image Translation via Signed Attribute Vectors","date":"2020-11-02","arxiv_id":"2011.01215","repositories_listed":1,"syntology":null},{"url":"/paper/exploring-generative-adversarial-networks-for","slug":"exploring-generative-adversarial-networks-for","title":"Exploring Generative Adversarial Networks for Image-to-Image Translation in STEM Simulation","date":"2020-10-29","arxiv_id":"2010.15315","repositories_listed":1,"syntology":null},{"url":"/paper/ipu-net-multi-scale-identity-preserved-u-net","slug":"ipu-net-multi-scale-identity-preserved-u-net","title":"Multi Scale Identity-Preserving Image-to-Image Translation Network for Low-Resolution Face Recognition","date":"2020-10-23","arxiv_id":"2010.12249","repositories_listed":1,"syntology":null},{"url":"/paper/synthesis-of-covid-19-chest-x-rays-using","slug":"synthesis-of-covid-19-chest-x-rays-using","title":"Synthesis of COVID-19 Chest X-rays using Unpaired Image-to-Image Translation","date":"2020-10-20","arxiv_id":"2010.10266","repositories_listed":1,"syntology":null},{"url":"/paper/procedural-3d-terrain-generation-using","slug":"procedural-3d-terrain-generation-using","title":"Procedural 3D Terrain Generation using Generative Adversarial Networks","date":"2020-10-13","arxiv_id":"2010.06411","repositories_listed":1,"syntology":null},{"url":"/paper/spectral-synthesis-for-satellite-to-satellite-1","slug":"spectral-synthesis-for-satellite-to-satellite-1","title":"Spectral Synthesis for Satellite-to-Satellite Translation","date":"2020-10-12","arxiv_id":"2010.06045","repositories_listed":1,"syntology":null},{"url":"/paper/unsupervised-image-to-image-translation-via","slug":"unsupervised-image-to-image-translation-via","title":"Unsupervised Image-to-Image Translation via Pre-trained StyleGAN2 Network","date":"2020-10-12","arxiv_id":"2010.05713","repositories_listed":1,"syntology":null},{"url":"/paper/balagan-image-translation-between-imbalanced-1","slug":"balagan-image-translation-between-imbalanced-1","title":"BalaGAN: Image Translation Between Imbalanced Domains via Cross-Modal Transfer","date":"2020-10-05","arxiv_id":"2010.02036","repositories_listed":1,"syntology":null},{"url":"/paper/image-translation-for-medical-image","slug":"image-translation-for-medical-image","title":"Image Translation for Medical Image Generation -- Ischemic Stroke Lesions","date":"2020-10-05","arxiv_id":"2010.02745","repositories_listed":1,"syntology":null},{"url":"/paper/deep-cyclic-generative-adversarial-residual","slug":"deep-cyclic-generative-adversarial-residual","title":"Deep Cyclic Generative Adversarial Residual Convolutional Networks for Real Image Super-Resolution","date":"2020-09-07","arxiv_id":"2009.03693","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/deep-cyclic-generative-adversarial-residual#ran","syntology_url":"https://syntology.ai/paper/2009.03693","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2009.03693"}},"official":{"repos":["RaoUmer/SRResCycGAN"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/sketchpatch-sketch-stylization-via-seamless","slug":"sketchpatch-sketch-stylization-via-seamless","title":"SketchPatch: Sketch Stylization via Seamless Patch-level Synthesis","date":"2020-09-04","arxiv_id":"2009.02216","repositories_listed":1,"syntology":null},{"url":"/paper/deepfacepencil-creating-face-images-from","slug":"deepfacepencil-creating-face-images-from","title":"DeepFacePencil: Creating Face Images from Freehand Sketches","date":"2020-08-31","arxiv_id":"2008.13343","repositories_listed":1,"syntology":null},{"url":"/paper/anime-to-real-clothing-cosplay-costume","slug":"anime-to-real-clothing-cosplay-costume","title":"Anime-to-Real Clothing: Cosplay Costume Generation via Image-to-Image Translation","date":"2020-08-26","arxiv_id":"2008.11479","repositories_listed":1,"syntology":null},{"url":"/paper/nas-dip-learning-deep-image-prior-with-neural","slug":"nas-dip-learning-deep-image-prior-with-neural","title":"NAS-DIP: Learning Deep Image Prior with Neural Architecture Search","date":"2020-08-26","arxiv_id":"2008.11713","repositories_listed":1,"syntology":null},{"url":"/paper/dynamic-object-removal-and-spatio-temporal","slug":"dynamic-object-removal-and-spatio-temporal","title":"Dynamic Object Removal and Spatio-Temporal RGB-D Inpainting via Geometry-Aware Adversarial Learning","date":"2020-08-12","arxiv_id":"2008.05058","repositories_listed":1,"syntology":null},{"url":"/paper/retrieval-guided-unsupervised-multi-domain","slug":"retrieval-guided-unsupervised-multi-domain","title":"Retrieval Guided Unsupervised Multi-domain Image-to-Image Translation","date":"2020-08-11","arxiv_id":"2008.04991","repositories_listed":1,"syntology":null},{"url":"/paper/describe-what-to-change-a-text-guided","slug":"describe-what-to-change-a-text-guided","title":"Describe What to Change: A Text-guided Unsupervised Image-to-Image Translation Approach","date":"2020-08-10","arxiv_id":"2008.04200","repositories_listed":1,"syntology":null},{"url":"/paper/domain-specific-mappings-for-generative","slug":"domain-specific-mappings-for-generative","title":"Domain-Specific Mappings for Generative Adversarial Style Transfer","date":"2020-08-05","arxiv_id":"2008.02198","repositories_listed":1,"syntology":null},{"url":"/paper/synthetic-to-real-unsupervised-domain","slug":"synthetic-to-real-unsupervised-domain","title":"An Unsupervised Domain Adaptation Scheme for Single-Stage Artwork Recognition in Cultural Sites","date":"2020-08-04","arxiv_id":"2008.01882","repositories_listed":1,"syntology":null},{"url":"/paper/content-consistent-matching-for-domain","slug":"content-consistent-matching-for-domain","title":"Content-Consistent Matching for Domain Adaptive Semantic Segmentation","date":"2020-08-01","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/joint-low-dose-ct-denoising-and-kidney","slug":"joint-low-dose-ct-denoising-and-kidney","title":"Joint Low Dose CT Denoising And Kidney Segmentation","date":"2020-07-31","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/learning-from-scale-invariant-examples-for","slug":"learning-from-scale-invariant-examples-for","title":"Learning from Scale-Invariant Examples for Domain Adaptation in Semantic Segmentation","date":"2020-07-28","arxiv_id":"2007.14449","repositories_listed":1,"syntology":null},{"url":"/paper/toward-zero-shot-unsupervised-image-to-image","slug":"toward-zero-shot-unsupervised-image-to-image","title":"Toward Zero-Shot Unsupervised Image-to-Image Translation","date":"2020-07-28","arxiv_id":"2007.14050","repositories_listed":1,"syntology":null},{"url":"/paper/tsit-a-simple-and-versatile-framework-for","slug":"tsit-a-simple-and-versatile-framework-for","title":"TSIT: A Simple and Versatile Framework for Image-to-Image Translation","date":"2020-07-23","arxiv_id":"2007.12072","repositories_listed":1,"syntology":null},{"url":"/paper/classes-matter-a-fine-grained-adversarial","slug":"classes-matter-a-fine-grained-adversarial","title":"Classes Matter: A Fine-grained Adversarial Approach to Cross-domain Semantic Segmentation","date":"2020-07-17","arxiv_id":"2007.09222","repositories_listed":1,"syntology":null},{"url":"/paper/coco-funit-few-shot-unsupervised-image","slug":"coco-funit-few-shot-unsupervised-image","title":"COCO-FUNIT: Few-Shot Unsupervised Image Translation with a Content Conditioned Style Encoder","date":"2020-07-15","arxiv_id":"2007.07431","repositories_listed":1,"syntology":null},{"url":"/paper/transformation-consistency-regularization-a","slug":"transformation-consistency-regularization-a","title":"Transformation Consistency Regularization- A Semi-Supervised Paradigm for Image-to-Image Translation","date":"2020-07-15","arxiv_id":"2007.07867","repositories_listed":1,"syntology":null},{"url":"/paper/lightweight-modules-for-efficient-deep","slug":"lightweight-modules-for-efficient-deep","title":"Lightweight Modules for Efficient Deep Learning based Image Restoration","date":"2020-07-11","arxiv_id":"2007.05835","repositories_listed":1,"syntology":null},{"url":"/paper/learning-the-prediction-distribution-for-semi","slug":"learning-the-prediction-distribution-for-semi","title":"Learning the Prediction Distribution for Semi-Supervised Learning with Normalising Flows","date":"2020-07-06","arxiv_id":"2007.02745","repositories_listed":1,"syntology":null},{"url":"/paper/mcmi-multi-cycle-image-translation-with","slug":"mcmi-multi-cycle-image-translation-with","title":"MCMI: Multi-Cycle Image Translation with Mutual Information Constraints","date":"2020-07-06","arxiv_id":"2007.02919","repositories_listed":1,"syntology":null},{"url":"/paper/deep-single-image-manipulation","slug":"deep-single-image-manipulation","title":"Image Shape Manipulation from a Single Augmented Training Sample","date":"2020-07-02","arxiv_id":"2007.01289","repositories_listed":1,"syntology":null},{"url":"/paper/icam-interpretable-classification-via","slug":"icam-interpretable-classification-via","title":"ICAM: Interpretable Classification via Disentangled Representations and Feature Attribution Mapping","date":"2020-06-15","arxiv_id":"2006.08287","repositories_listed":1,"syntology":{"n":1,"n_ran":0,"n_constructed":0,"n_ran_checked":0,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"0 ran · 1 unverified","sample_list":"/paper/icam-interpretable-classification-via#ran","syntology_url":"https://syntology.ai/paper/2006.08287","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2006.08287"}},"official":{"repos":["CherBass/ICAM"],"state":"official: harvested, nothing ran","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":[]}}},{"url":"/paper/2d-image-relighting-with-image-to-image","slug":"2d-image-relighting-with-image-to-image","title":"2D Image Relighting with Image-to-Image Translation","date":"2020-06-14","arxiv_id":"2006.07816","repositories_listed":1,"syntology":null},{"url":"/paper/comir-contrastive-multimodal-image","slug":"comir-contrastive-multimodal-image","title":"CoMIR: Contrastive Multimodal Image Representation for Registration","date":"2020-06-11","arxiv_id":"2006.06325","repositories_listed":1,"syntology":null},{"url":"/paper/rethinking-the-truly-unsupervised-image-to","slug":"rethinking-the-truly-unsupervised-image-to","title":"Rethinking the Truly Unsupervised Image-to-Image Translation","date":"2020-06-11","arxiv_id":"2006.06500","repositories_listed":1,"syntology":null},{"url":"/paper/gans-in-computer-vision-ebook","slug":"gans-in-computer-vision-ebook","title":"GANs in computer vision ebook","date":"2020-06-10","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/novel-object-viewpoint-estimation-through-1","slug":"novel-object-viewpoint-estimation-through-1","title":"Novel Object Viewpoint Estimation through Reconstruction Alignment","date":"2020-06-05","arxiv_id":"2006.03586","repositories_listed":1,"syntology":null},{"url":"/paper/ear2face-deep-biometric-modality-mapping","slug":"ear2face-deep-biometric-modality-mapping","title":"Ear2Face: Deep Biometric Modality Mapping","date":"2020-06-02","arxiv_id":"2006.01943","repositories_listed":1,"syntology":null},{"url":"/paper/breaking-the-cycle-colleagues-are-all-you-1","slug":"breaking-the-cycle-colleagues-are-all-you-1","title":"Breaking the Cycle - Colleagues Are All You Need","date":"2020-06-01","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/deep-generation-of-face-images-from-sketches","slug":"deep-generation-of-face-images-from-sketches","title":"Deep Generation of Face Images from Sketches","date":"2020-06-01","arxiv_id":"2006.01047","repositories_listed":1,"syntology":null},{"url":"/paper/dunit-detection-based-unsupervised-image-to","slug":"dunit-detection-based-unsupervised-image-to","title":"DUNIT: Detection-Based Unsupervised Image-to-Image Translation","date":"2020-06-01","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/network-fusion-for-content-creation-with","slug":"network-fusion-for-content-creation-with","title":"Network-to-Network Translation with Conditional Invertible Neural Networks","date":"2020-05-27","arxiv_id":"2005.13580","repositories_listed":1,"syntology":null},{"url":"/paper/deephist-differentiable-joint-and-color","slug":"deephist-differentiable-joint-and-color","title":"DeepHist: Differentiable Joint and Color Histogram Layers for Image-to-Image Translation","date":"2020-05-06","arxiv_id":"2005.03995","repositories_listed":1,"syntology":null},{"url":"/paper/stereogan-bridging-synthetic-to-real-domain","slug":"stereogan-bridging-synthetic-to-real-domain","title":"StereoGAN: Bridging Synthetic-to-Real Domain Gap by Joint Optimization of Domain Translation and Stereo Matching","date":"2020-05-05","arxiv_id":"2005.01927","repositories_listed":1,"syntology":null},{"url":"/paper/desmoking-laparoscopy-surgery-images-using-an","slug":"desmoking-laparoscopy-surgery-images-using-an","title":"Desmoking laparoscopy surgery images using an image-to-image translation guided by an embedded dark channel","date":"2020-04-19","arxiv_id":"2004.08947","repositories_listed":1,"syntology":null},{"url":"/paper/rpnet-a-deep-learning-approach-for-robust-r","slug":"rpnet-a-deep-learning-approach-for-robust-r","title":"RPnet: A Deep Learning approach for robust R Peak detection in noisy ECG","date":"2020-04-17","arxiv_id":"2004.08103","repositories_listed":1,"syntology":null},{"url":"/paper/melanoma-detection-using-adversarial-training","slug":"melanoma-detection-using-adversarial-training","title":"Melanoma Detection using Adversarial Training and Deep Transfer Learning","date":"2020-04-14","arxiv_id":"2004.06824","repositories_listed":1,"syntology":null},{"url":"/paper/melanoma-detection-using-adversarial-training-1","slug":"melanoma-detection-using-adversarial-training-1","title":"Melanoma Detection using Adversarial Training and Deep Transfer Learning","date":"2020-04-14","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/sesame-semantic-editing-of-scenes-by-adding","slug":"sesame-semantic-editing-of-scenes-by-adding","title":"SESAME: Semantic Editing of Scenes by Adding, Manipulating or Erasing Objects","date":"2020-04-10","arxiv_id":"2004.04977","repositories_listed":1,"syntology":null},{"url":"/paper/tuigan-learning-versatile-image-to-image","slug":"tuigan-learning-versatile-image-to-image","title":"TuiGAN: Learning Versatile Image-to-Image Translation with Two Unpaired Images","date":"2020-04-09","arxiv_id":"2004.04634","repositories_listed":1,"syntology":null},{"url":"/paper/toward-fine-grained-facial-expression","slug":"toward-fine-grained-facial-expression","title":"Toward Fine-grained Facial Expression Manipulation","date":"2020-04-07","arxiv_id":"2004.03132","repositories_listed":1,"syntology":null},{"url":"/paper/structural-analogy-from-a-single-image-pair","slug":"structural-analogy-from-a-single-image-pair","title":"Structural-analogy from a Single Image Pair","date":"2020-04-05","arxiv_id":"2004.02222","repositories_listed":1,"syntology":null},{"url":"/paper/towards-lifelong-self-supervision-for","slug":"towards-lifelong-self-supervision-for","title":"Towards Lifelong Self-Supervision For Unpaired Image-to-Image Translation","date":"2020-03-31","arxiv_id":"2004.00161","repositories_listed":1,"syntology":null},{"url":"/paper/semi-supervised-learning-for-few-shot-image","slug":"semi-supervised-learning-for-few-shot-image","title":"Semi-supervised Learning for Few-shot Image-to-Image Translation","date":"2020-03-30","arxiv_id":"2003.13853","repositories_listed":1,"syntology":null},{"url":"/paper/augmenting-colonoscopy-using-extended-and","slug":"augmenting-colonoscopy-using-extended-and","title":"Augmenting Colonoscopy using Extended and Directional CycleGAN for Lossy Image Translation","date":"2020-03-27","arxiv_id":"2003.12473","repositories_listed":1,"syntology":null},{"url":"/paper/log-likelihood-ratio-minimizing-flows-towards","slug":"log-likelihood-ratio-minimizing-flows-towards","title":"Log-Likelihood Ratio Minimizing Flows: Towards Robust and Quantifiable Neural Distribution Alignment","date":"2020-03-26","arxiv_id":"2003.12170","repositories_listed":1,"syntology":null},{"url":"/paper/high-resolution-daytime-translation-without","slug":"high-resolution-daytime-translation-without","title":"High-Resolution Daytime Translation Without Domain Labels","date":"2020-03-19","arxiv_id":"2003.08791","repositories_listed":1,"syntology":null},{"url":"/paper/unsupervised-multi-modal-image-registration","slug":"unsupervised-multi-modal-image-registration","title":"Unsupervised Multi-Modal Image Registration via Geometry Preserving Image-to-Image Translation","date":"2020-03-18","arxiv_id":"2003.08073","repositories_listed":1,"syntology":null},{"url":"/paper/gmm-unit-unsupervised-multi-domain-and-multi-1","slug":"gmm-unit-unsupervised-multi-domain-and-multi-1","title":"GMM-UNIT: Unsupervised Multi-Domain and Multi-Modal Image-to-Image Translation via Attribute Gaussian Mixture Modeling","date":"2020-03-15","arxiv_id":"2003.06788","repositories_listed":1,"syntology":null},{"url":"/paper/a-mobile-robot-hand-arm-teleoperation-system","slug":"a-mobile-robot-hand-arm-teleoperation-system","title":"A Mobile Robot Hand-Arm Teleoperation System by Vision and IMU","date":"2020-03-11","arxiv_id":"2003.05212","repositories_listed":1,"syntology":null},{"url":"/paper/deepurl-deep-pose-estimation-framework-for","slug":"deepurl-deep-pose-estimation-framework-for","title":"DeepURL: Deep Pose Estimation Framework for Underwater Relative Localization","date":"2020-03-11","arxiv_id":"2003.05523","repositories_listed":1,"syntology":null},{"url":"/paper/lc-gan-image-to-image-translation-based-on","slug":"lc-gan-image-to-image-translation-based-on","title":"LC-GAN: Image-to-image Translation Based on Generative Adversarial Network for Endoscopic Images","date":"2020-03-10","arxiv_id":"2003.04949","repositories_listed":1,"syntology":null},{"url":"/paper/learning-to-transfer-texture-from-clothing","slug":"learning-to-transfer-texture-from-clothing","title":"Learning to Transfer Texture from Clothing Images to 3D Humans","date":"2020-03-04","arxiv_id":"2003.02050","repositories_listed":1,"syntology":null},{"url":"/paper/ganhopper-multi-hop-gan-for-unsupervised","slug":"ganhopper-multi-hop-gan-for-unsupervised","title":"GANHopper: Multi-Hop GAN for Unsupervised Image-to-Image Translation","date":"2020-02-24","arxiv_id":"2002.10102","repositories_listed":1,"syntology":null},{"url":"/paper/leafgan-an-effective-data-augmentation-method","slug":"leafgan-an-effective-data-augmentation-method","title":"LeafGAN: An Effective Data Augmentation Method for Practical Plant Disease Diagnosis","date":"2020-02-24","arxiv_id":"2002.10100","repositories_listed":1,"syntology":null},{"url":"/paper/driver-gaze-estimation-in-the-real-world","slug":"driver-gaze-estimation-in-the-real-world","title":"Gaze Preserving CycleGANs for Eyeglass Removal & Persistent Gaze Estimation","date":"2020-02-06","arxiv_id":"2002.02077","repositories_listed":1,"syntology":null},{"url":"/paper/multi-channel-attention-selection-gans-for","slug":"multi-channel-attention-selection-gans-for","title":"Multi-Channel Attention Selection GANs for Guided Image-to-Image Translation","date":"2020-02-03","arxiv_id":"2002.01048","repositories_listed":1,"syntology":null},{"url":"/paper/asymmetric-generative-adversarial-networks","slug":"asymmetric-generative-adversarial-networks","title":"Asymmetric GANs for Image-to-Image Translation","date":"2019-12-14","arxiv_id":"1912.06931","repositories_listed":1,"syntology":null},{"url":"/paper/unified-generative-adversarial-networks-for","slug":"unified-generative-adversarial-networks-for","title":"Unified Generative Adversarial Networks for Controllable Image-to-Image Translation","date":"2019-12-12","arxiv_id":"1912.06112","repositories_listed":1,"syntology":null},{"url":"/paper/exploring-unlabeled-faces-for-novel-attribute","slug":"exploring-unlabeled-faces-for-novel-attribute","title":"Exploring Unlabeled Faces for Novel Attribute Discovery","date":"2019-12-06","arxiv_id":"1912.03085","repositories_listed":1,"syntology":null},{"url":"/paper/breaking-the-cycle-colleagues-are-all-you","slug":"breaking-the-cycle-colleagues-are-all-you","title":"Breaking the cycle -- Colleagues are all you need","date":"2019-11-24","arxiv_id":"1911.10538","repositories_listed":1,"syntology":null},{"url":"/paper/edit-exemplar-domain-aware-image-to-image","slug":"edit-exemplar-domain-aware-image-to-image","title":"EDIT: Exemplar-Domain Aware Image-to-Image Translation","date":"2019-11-24","arxiv_id":"1911.10520","repositories_listed":1,"syntology":null},{"url":"/paper/using-u-nets-to-create-high-fidelity-virtual","slug":"using-u-nets-to-create-high-fidelity-virtual","title":"Using U-Nets to Create High-Fidelity Virtual Observations of the Solar Corona","date":"2019-11-10","arxiv_id":"1911.04006","repositories_listed":1,"syntology":null},{"url":"/paper/unsupervised-multi-domain-multimodal-image-to","slug":"unsupervised-multi-domain-multimodal-image-to","title":"Unsupervised Multi-Domain Multimodal Image-to-Image Translation with Explicit Domain-Constrained Disentanglement","date":"2019-11-02","arxiv_id":"1911.00622","repositories_listed":1,"syntology":null},{"url":"/paper/guided-image-to-image-translation-with-bi-1","slug":"guided-image-to-image-translation-with-bi-1","title":"Guided Image-to-Image Translation with Bi-Directional Feature Transformation","date":"2019-10-24","arxiv_id":"1910.11328","repositories_listed":1,"syntology":null},{"url":"/paper/learning-to-predict-layout-to-image","slug":"learning-to-predict-layout-to-image","title":"Learning to Predict Layout-to-image Conditional Convolutions for Semantic Image Synthesis","date":"2019-10-15","arxiv_id":"1910.06809","repositories_listed":1,"syntology":null},{"url":"/paper/adversarial-pulmonary-pathology-translation","slug":"adversarial-pulmonary-pathology-translation","title":"Adversarial Pulmonary Pathology Translation for Pairwise Chest X-ray Data Augmentation","date":"2019-10-11","arxiv_id":"1910.04961","repositories_listed":1,"syntology":null},{"url":"/paper/extremely-weak-supervised-image-to-image","slug":"extremely-weak-supervised-image-to-image","title":"Extremely Weak Supervised Image-to-Image Translation for Semantic Segmentation","date":"2019-09-18","arxiv_id":"1909.08542","repositories_listed":1,"syntology":null},{"url":"/paper/multi-mapping-image-to-image-translation-via","slug":"multi-mapping-image-to-image-translation-via","title":"Multi-mapping Image-to-Image Translation via Learning Disentanglement","date":"2019-09-17","arxiv_id":"1909.07877","repositories_listed":1,"syntology":{"n":5,"n_ran":2,"n_constructed":0,"n_ran_checked":2,"n_instrument":0,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/multi-mapping-image-to-image-translation-via#ran","syntology_url":"https://syntology.ai/paper/1909.07877","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1909.07877"}},"official":{"repos":["Xiaoming-Yu/DMIT"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/poly-gan-multi-conditioned-gan-for-fashion","slug":"poly-gan-multi-conditioned-gan-for-fashion","title":"Poly-GAN: Multi-Conditioned GAN for Fashion Synthesis","date":"2019-09-05","arxiv_id":"1909.02165","repositories_listed":1,"syntology":null},{"url":"/paper/multi-modal-fusion-for-end-to-end-rgb-t","slug":"multi-modal-fusion-for-end-to-end-rgb-t","title":"Multi-Modal Fusion for End-to-End RGB-T Tracking","date":"2019-08-30","arxiv_id":"1908.11714","repositories_listed":1,"syntology":null},{"url":"/paper/planning-beyond-the-sensing-horizon-using-a","slug":"planning-beyond-the-sensing-horizon-using-a","title":"Planning Beyond the Sensing Horizon Using a Learned Context","date":"2019-08-24","arxiv_id":"1908.09171","repositories_listed":1,"syntology":null},{"url":"/paper/a-tour-of-convolutional-networks-guided-by","slug":"a-tour-of-convolutional-networks-guided-by","title":"A Tour of Convolutional Networks Guided by Linear Interpreters","date":"2019-08-14","arxiv_id":"1908.05168","repositories_listed":1,"syntology":null},{"url":"/paper/adversarial-self-defense-for-cycle-consistent","slug":"adversarial-self-defense-for-cycle-consistent","title":"Adversarial Self-Defense for Cycle-Consistent GANs","date":"2019-08-05","arxiv_id":"1908.01517","repositories_listed":1,"syntology":null},{"url":"/paper/blind-deblurring-using-gans","slug":"blind-deblurring-using-gans","title":"Blind Deblurring Using GANs","date":"2019-07-27","arxiv_id":"1907.11880","repositories_listed":1,"syntology":null},{"url":"/paper/y-autoencoders-disentangling-latent","slug":"y-autoencoders-disentangling-latent","title":"Y-Autoencoders: disentangling latent representations via sequential-encoding","date":"2019-07-25","arxiv_id":"1907.10949","repositories_listed":1,"syntology":null},{"url":"/paper/cross-domain-car-detection-using-unsupervised","slug":"cross-domain-car-detection-using-unsupervised","title":"Cross-Domain Car Detection Using Unsupervised Image-to-Image Translation: From Day to Night","date":"2019-07-19","arxiv_id":"1907.08719","repositories_listed":1,"syntology":null},{"url":"/paper/artifact-disentanglement-network-for","slug":"artifact-disentanglement-network-for","title":"Artifact Disentanglement Network for Unsupervised Metal Artifact Reduction","date":"2019-06-05","arxiv_id":"1906.01806","repositories_listed":1,"syntology":null},{"url":"/paper/190600184","slug":"190600184","title":"ZstGAN: An Adversarial Approach for Unsupervised Zero-Shot Image-to-Image Translation","date":"2019-06-01","arxiv_id":"1906.00184","repositories_listed":1,"syntology":null},{"url":"/paper/enhanced-pix2pix-dehazing-network","slug":"enhanced-pix2pix-dehazing-network","title":"Enhanced Pix2pix Dehazing Network","date":"2019-06-01","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/homomorphic-latent-space-interpolation-for","slug":"homomorphic-latent-space-interpolation-for","title":"Homomorphic Latent Space Interpolation for Unpaired Image-To-Image Translation","date":"2019-06-01","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/borrow-from-anywhere-pseudo-multi-modal","slug":"borrow-from-anywhere-pseudo-multi-modal","title":"Borrow from Anywhere: Pseudo Multi-modal Object Detection in Thermal Imagery","date":"2019-05-21","arxiv_id":"1905.08789","repositories_listed":1,"syntology":null},{"url":"/paper/lidar-sensor-modeling-and-data-augmentation","slug":"lidar-sensor-modeling-and-data-augmentation","title":"LiDAR Sensor modeling and Data augmentation with GANs for Autonomous driving","date":"2019-05-17","arxiv_id":"1905.07290","repositories_listed":1,"syntology":null},{"url":"/paper/label-noise-robust-multi-domain-image-to","slug":"label-noise-robust-multi-domain-image-to","title":"Label-Noise Robust Multi-Domain Image-to-Image Translation","date":"2019-05-06","arxiv_id":"1905.02185","repositories_listed":1,"syntology":null}],"record_sha256":"c0b70a76a30b6711adf949e311a52d8d0a068b45496c3db111bd6b336f5a53a0","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}