{"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":"/method/patchgan/papers/2","list_of":"/method/patchgan","method":"PatchGAN","archive":{"snapshot":"2025-07-28"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"date (newest first), then slug","page":2,"pages_in_order":6,"rows_per_page":100,"rows":[101,200],"of":516,"counts":{"archive_papers_tagged":516,"with_a_code_link":169,"where_syntology_ran_a_sample":16,"not_listed_spam_title":0,"listed":516,"listed_where_code_ran":16,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":14,"every_run_a_failure_of_syntologys_instrument":2,"listed_with_a_run_with_no_instrument_failure":14,"listed_every_run_a_failure_of_syntologys_instrument":2,"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":"/method/patchgan","prev":"/method/patchgan","next":"/method/patchgan/papers/3","papers":[{"paper":"/paper/tsgan-an-optical-to-sar-dual-conditional-gan","slug":"tsgan-an-optical-to-sar-dual-conditional-gan","title":"TSGAN: An Optical-to-SAR Dual Conditional GAN for Optical based SAR Temporal Shifting","date":"2023-12-31","arxiv_id":"2401.00440","n_code_links":1,"syntology":null},{"paper":null,"slug":"cyclegan-models-for-mri-image-translation","title":"CycleGAN Models for MRI Image Translation","date":"2023-12-28","arxiv_id":"2401.00023","n_code_links":0,"syntology":null},{"paper":null,"slug":"compressing-image-to-image-translation-gans","title":"Compressing Image-to-Image Translation GANs Using Local Density Structures on Their Learned Manifold","date":"2023-12-22","arxiv_id":"2312.14776","n_code_links":0,"syntology":null},{"paper":"/paper/ultrasound-image-enhancement-using-cyclegan","slug":"ultrasound-image-enhancement-using-cyclegan","title":"Ultrasound Image Enhancement using CycleGAN and Perceptual Loss","date":"2023-12-18","arxiv_id":"2312.11748","n_code_links":1,"syntology":null},{"paper":"/paper/phendiff-revealing-invisible-phenotypes-with","slug":"phendiff-revealing-invisible-phenotypes-with","title":"PhenDiff: Revealing Subtle Phenotypes with Diffusion Models in Real Images","date":"2023-12-13","arxiv_id":"2312.08290","n_code_links":1,"syntology":{"ran":5,"of":8,"n_ran_checked":5,"n_instrument":0,"unverified":3,"pointer_only":8,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 0 violated, 5 with no contract checked; 0 where Syntology's instrument failed) · 3 unverified","official":{"repos":["warmongeringbeaver/phendiff"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":3,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"mri-scan-synthesis-methods-based-on","title":"MRI Scan Synthesis Methods based on Clustering and Pix2Pix","date":"2023-12-08","arxiv_id":"2312.05176","n_code_links":0,"syntology":null},{"paper":"/paper/editable-stain-transformation-of-histological","slug":"editable-stain-transformation-of-histological","title":"Editable Stain Transformation Of Histological Images Using Unpaired GANs","date":"2023-12-06","arxiv_id":"2312.03647","n_code_links":1,"syntology":null},{"paper":"/paper/stereofog-computational-defogging-via-image","slug":"stereofog-computational-defogging-via-image","title":"STEREOFOG -- Computational DeFogging via Image-to-Image Translation on a real-world Dataset","date":"2023-12-04","arxiv_id":"2312.02344","n_code_links":1,"syntology":null},{"paper":"/paper/pipeline-enabling-zero-shot-classification","slug":"pipeline-enabling-zero-shot-classification","title":"Pipeline Enabling Zero-shot Classification for Bangla Handwritten Grapheme","date":"2023-12-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"towards-ultra-low-cost-smartphone-microscopy","title":"Towards ultra-low-cost smartphone microscopy","date":"2023-11-28","arxiv_id":"2312.11479","n_code_links":0,"syntology":null},{"paper":null,"slug":"automated-3d-tumor-segmentation-using","title":"Automated 3D Tumor Segmentation using Temporal Cubic PatchGAN (TCuP-GAN)","date":"2023-11-23","arxiv_id":"2311.14148","n_code_links":0,"syntology":null},{"paper":"/paper/oct2confocal-3d-cyclegan-based-translation-of","slug":"oct2confocal-3d-cyclegan-based-translation-of","title":"OCT2Confocal: 3D CycleGAN based Translation of Retinal OCT Images to Confocal Microscopy","date":"2023-11-17","arxiv_id":"2311.10902","n_code_links":2,"syntology":null},{"paper":null,"slug":"a-novel-1d-generative-adversarial-network","title":"A Novel 1D Generative Adversarial Network-based Framework for Atrial Fibrillation Detection using Restored Wrist Photoplethysmography Signals","date":"2023-11-13","arxiv_id":"2312.09459","n_code_links":0,"syntology":null},{"paper":"/paper/cycleganas-differentiable-neural-architecture","slug":"cycleganas-differentiable-neural-architecture","title":"CycleGANAS: Differentiable Neural Architecture Search for CycleGAN","date":"2023-11-13","arxiv_id":"2311.07162","n_code_links":1,"syntology":null},{"paper":null,"slug":"synthesizing-bidirectional-temporal-states-of","title":"Synthesizing Bidirectional Temporal States of Knee Osteoarthritis Radiographs with Cycle-Consistent Generative Adversarial Neural Networks","date":"2023-11-10","arxiv_id":"2311.05798","n_code_links":0,"syntology":null},{"paper":null,"slug":"let-s-get-the-facs-straight-reconstructing","title":"Let's Get the FACS Straight -- Reconstructing Obstructed Facial Features","date":"2023-11-09","arxiv_id":"2311.05221","n_code_links":0,"syntology":null},{"paper":"/paper/a-two-stage-generative-model-with-cyclegan","slug":"a-two-stage-generative-model-with-cyclegan","title":"A Two-Stage Generative Model with CycleGAN and Joint Diffusion for MRI-based Brain Tumor Detection","date":"2023-11-06","arxiv_id":"2311.03074","n_code_links":1,"syntology":null},{"paper":"/paper/deep-image-semantic-communication-model-for","slug":"deep-image-semantic-communication-model-for","title":"Deep Image Semantic Communication Model for Artificial Intelligent Internet of Things","date":"2023-11-06","arxiv_id":"2311.02926","n_code_links":2,"syntology":null},{"paper":null,"slug":"novel-view-synthesis-from-a-single-rgbd-image","title":"Novel View Synthesis from a Single RGBD Image for Indoor Scenes","date":"2023-11-02","arxiv_id":"2311.01065","n_code_links":0,"syntology":null},{"paper":"/paper/feature-oriented-deep-learning-framework-for","slug":"feature-oriented-deep-learning-framework-for","title":"Feature-oriented Deep Learning Framework for Pulmonary Cone-beam CT (CBCT) Enhancement with Multi-task Customized Perceptual Loss","date":"2023-11-01","arxiv_id":"2311.00412","n_code_links":1,"syntology":null},{"paper":null,"slug":"single-channel-speech-enhancement-by-colored","title":"Single channel speech enhancement by colored spectrograms","date":"2023-10-26","arxiv_id":"2310.17142","n_code_links":0,"syntology":null},{"paper":null,"slug":"dt-mars-cyclegan-improved-object-detection","title":"DT/MARS-CycleGAN: Improved Object Detection for MARS Phenotyping Robot","date":"2023-10-19","arxiv_id":"2310.12787","n_code_links":0,"syntology":null},{"paper":null,"slug":"attribute-localization-and-revision-network","title":"Attribute Localization and Revision Network for Zero-Shot Learning","date":"2023-10-11","arxiv_id":"2310.07548","n_code_links":0,"syntology":null},{"paper":null,"slug":"brainvoxgen-deep-learning-framework-for","title":"BrainVoxGen: Deep learning framework for synthesis of Ultrasound to MRI","date":"2023-10-11","arxiv_id":"2310.08608","n_code_links":0,"syntology":null},{"paper":null,"slug":"crowd-counting-in-harsh-weather-using-image","title":"Crowd Counting in Harsh Weather using Image Denoising with Pix2Pix GANs","date":"2023-10-11","arxiv_id":"2310.07245","n_code_links":0,"syntology":null},{"paper":null,"slug":"lroc-pangu-gan-closing-the-simulation-gap-in","title":"LROC-PANGU-GAN: Closing the Simulation Gap in Learning Crater Segmentation with Planetary Simulators","date":"2023-10-04","arxiv_id":"2310.02781","n_code_links":0,"syntology":null},{"paper":"/paper/prompt-based-test-time-real-image-dehazing-a","slug":"prompt-based-test-time-real-image-dehazing-a","title":"Prompt-based test-time real image dehazing: a novel pipeline","date":"2023-09-29","arxiv_id":"2309.17389","n_code_links":1,"syntology":null},{"paper":null,"slug":"stochastic-digital-twin-for-copy-detection","title":"Stochastic Digital Twin for Copy Detection Patterns","date":"2023-09-28","arxiv_id":"2309.16866","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-novel-deep-learning-technique-for","title":"A Novel Deep Learning Technique for Morphology Preserved Fetal ECG Extraction from Mother ECG using 1D-CycleGAN","date":"2023-09-25","arxiv_id":"2310.03759","n_code_links":0,"syntology":null},{"paper":"/paper/gamix-vae-a-vae-with-gaussian-mixture-based","slug":"gamix-vae-a-vae-with-gaussian-mixture-based","title":"How to train your VAE","date":"2023-09-22","arxiv_id":"2309.13160","n_code_links":1,"syntology":null},{"paper":null,"slug":"osnet-mneto-two-types-of-general","title":"OSNet & MNetO: Two Types of General Reconstruction Architectures for Linear Computed Tomography in Multi-Scenarios","date":"2023-09-21","arxiv_id":"2309.11858","n_code_links":0,"syntology":null},{"paper":null,"slug":"cross-modal-synthesis-of-structural-mri-and","title":"Cross-Modal Synthesis of Structural MRI and Functional Connectivity Networks via Conditional ViT-GANs","date":"2023-09-15","arxiv_id":"2309.08160","n_code_links":0,"syntology":null},{"paper":null,"slug":"hierarchical-level-rain-image-generative","title":"Hierarchical-level rain image generative model based on GAN","date":"2023-09-06","arxiv_id":"2309.02964","n_code_links":0,"syntology":null},{"paper":"/paper/constrained-cyclegan-for-effective-generation","slug":"constrained-cyclegan-for-effective-generation","title":"Constrained CycleGAN for Effective Generation of Ultrasound Sector Images of Improved Spatial Resolution","date":"2023-09-02","arxiv_id":"2309.00995","n_code_links":1,"syntology":null},{"paper":null,"slug":"segmentacao-e-contagem-de-troncos-de-madeira","title":"Segmentação e contagem de troncos de madeira utilizando deep learning e processamento de imagens","date":"2023-08-31","arxiv_id":"2309.00123","n_code_links":0,"syntology":null},{"paper":null,"slug":"ten-years-of-generative-adversarial-nets-gans","title":"Ten Years of Generative Adversarial Nets (GANs): A survey of the state-of-the-art","date":"2023-08-30","arxiv_id":"2308.16316","n_code_links":0,"syntology":null},{"paper":"/paper/denoising-diffusion-based-mr-to-ct-image","slug":"denoising-diffusion-based-mr-to-ct-image","title":"Denoising diffusion-based MRI to CT image translation enables automated spinal segmentation","date":"2023-08-18","arxiv_id":"2308.09345","n_code_links":1,"syntology":null},{"paper":null,"slug":"a-comparative-study-of-image-to-image","title":"A Comparative Study of Image-to-Image Translation Using GANs for Synthetic Child Race Data","date":"2023-08-08","arxiv_id":"2308.04232","n_code_links":0,"syntology":null},{"paper":"/paper/enhancing-visibility-in-nighttime-haze-images","slug":"enhancing-visibility-in-nighttime-haze-images","title":"Enhancing Visibility in Nighttime Haze Images Using Guided APSF and Gradient Adaptive Convolution","date":"2023-08-03","arxiv_id":"2308.01738","n_code_links":1,"syntology":{"ran":2,"of":3,"n_ran_checked":1,"n_instrument":1,"unverified":1,"pointer_only":3,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 1 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","official":{"repos":["jinyeying/nighttime_dehaze"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"focus-on-content-not-noise-improving-image","title":"Focus on Content not Noise: Improving Image Generation for Nuclei Segmentation by Suppressing Steganography in CycleGAN","date":"2023-08-03","arxiv_id":"2308.01769","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-deep-learning-approach-for-virtual-contrast","title":"A Deep Learning Approach for Virtual Contrast Enhancement in Contrast Enhanced Spectral Mammography","date":"2023-08-01","arxiv_id":"2308.00471","n_code_links":0,"syntology":null},{"paper":null,"slug":"mask-guided-data-augmentation-for","title":"Mask-guided Data Augmentation for Multiparametric MRI Generation with a Rare Hepatocellular Carcinoma","date":"2023-07-30","arxiv_id":"2307.16314","n_code_links":0,"syntology":null},{"paper":"/paper/structure-preserving-synthesis-maskgan-for","slug":"structure-preserving-synthesis-maskgan-for","title":"Structure-Preserving Synthesis: MaskGAN for Unpaired MR-CT Translation","date":"2023-07-30","arxiv_id":"2307.16143","n_code_links":1,"syntology":null},{"paper":"/paper/a-time-frequency-generative-adversarial-based","slug":"a-time-frequency-generative-adversarial-based","title":"A Time-Frequency Generative Adversarial based method for Audio Packet Loss Concealment","date":"2023-07-28","arxiv_id":"2307.15611","n_code_links":1,"syntology":null},{"paper":null,"slug":"volcanic-ash-delimitation-using-artificial","title":"Volcanic ash delimitation using Artificial Intelligence based on Pix2Pix","date":"2023-07-24","arxiv_id":"2307.12970","n_code_links":0,"syntology":null},{"paper":null,"slug":"development-of-pericardial-fat-count-images","title":"Development of pericardial fat count images using a combination of three different deep-learning models","date":"2023-07-23","arxiv_id":"2307.12316","n_code_links":0,"syntology":null},{"paper":null,"slug":"line-art-colorization-of-fakemon-using","title":"Line Art Colorization of Fakemon using Generative Adversarial Neural Networks","date":"2023-07-11","arxiv_id":"2307.05760","n_code_links":0,"syntology":null},{"paper":null,"slug":"multi-channel-feature-extraction-for-virtual","title":"Multi-Channel Feature Extraction for Virtual Histological Staining of Photon Absorption Remote Sensing Images","date":"2023-07-04","arxiv_id":"2307.01824","n_code_links":0,"syntology":null},{"paper":null,"slug":"xai-cyclegan-a-cycle-consistent-generative","title":"xAI-CycleGAN, a Cycle-Consistent Generative Assistive Network","date":"2023-06-27","arxiv_id":"2306.15760","n_code_links":0,"syntology":null},{"paper":"/paper/improving-panoptic-segmentation-for-nighttime","slug":"improving-panoptic-segmentation-for-nighttime","title":"Improving Panoptic Segmentation for Nighttime or Low-Illumination Urban Driving Scenes","date":"2023-06-23","arxiv_id":"2306.13725","n_code_links":1,"syntology":null},{"paper":null,"slug":"semantically-aware-mask-cyclegan-for","title":"Semantically-aware Mask CycleGAN for Translating Artistic Portraits to Photo-realistic Visualizations","date":"2023-06-11","arxiv_id":"2306.06577","n_code_links":0,"syntology":null},{"paper":null,"slug":"unpaired-deep-learning-for-pharmacokinetic","title":"Unpaired Deep Learning for Pharmacokinetic Parameter Estimation from Dynamic Contrast-Enhanced MRI","date":"2023-06-07","arxiv_id":"2306.04339","n_code_links":0,"syntology":null},{"paper":null,"slug":"rdfc-gan-rgb-depth-fusion-cyclegan-for-indoor","title":"RDFC-GAN: RGB-Depth Fusion CycleGAN for Indoor Depth Completion","date":"2023-06-06","arxiv_id":"2306.03584","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-vessel-segmentation-based-cyclegan-for","title":"A Vessel-Segmentation-Based CycleGAN for Unpaired Multi-modal Retinal Image Synthesis","date":"2023-06-05","arxiv_id":"2306.02901","n_code_links":0,"syntology":null},{"paper":"/paper/an-attentive-based-generative-model-for","slug":"an-attentive-based-generative-model-for","title":"An Attentive-based Generative Model for Medical Image Synthesis","date":"2023-06-02","arxiv_id":"2306.01562","n_code_links":1,"syntology":null},{"paper":null,"slug":"gans-and-alternative-methods-of-synthetic","title":"GANs and alternative methods of synthetic noise generation for domain adaption of defect classification of Non-destructive ultrasonic testing","date":"2023-06-02","arxiv_id":"2306.01469","n_code_links":0,"syntology":null},{"paper":null,"slug":"deep-transductive-transfer-learning-for","title":"Deep Transductive Transfer Learning for Automatic Target Recognition","date":"2023-05-23","arxiv_id":"2305.13886","n_code_links":0,"syntology":null},{"paper":null,"slug":"color-deconvolution-applied-to-domain","title":"Color Deconvolution applied to Domain Adaptation in HER2 histopathological images","date":"2023-05-12","arxiv_id":"2305.07404","n_code_links":0,"syntology":null},{"paper":null,"slug":"fishrecgan-an-end-to-end-gan-based-network","title":"FishRecGAN: An End to End GAN Based Network for Fisheye Rectification and Calibration","date":"2023-05-09","arxiv_id":"2305.05222","n_code_links":0,"syntology":null},{"paper":null,"slug":"synthesizing-pet-images-from-high-field-and","title":"Synthesizing PET images from High-field and Ultra-high-field MR images Using Joint Diffusion Attention Model","date":"2023-05-06","arxiv_id":"2305.03901","n_code_links":0,"syntology":null},{"paper":null,"slug":"automated-whole-slide-imaging-for-label-free","title":"Automated Whole Slide Imaging for Label-Free Histology using Photon Absorption Remote Sensing Microscopy","date":"2023-04-26","arxiv_id":"2304.13736","n_code_links":0,"syntology":null},{"paper":null,"slug":"bitrackgan-cascaded-cyclegans-to-constraint","title":"BiTrackGAN: Cascaded CycleGANs to Constraint Face Aging","date":"2023-04-22","arxiv_id":"2304.11313","n_code_links":0,"syntology":null},{"paper":null,"slug":"two-stage-mr-image-segmentation-method-for","title":"Two-stage MR Image Segmentation Method for Brain Tumors based on Attention Mechanism","date":"2023-04-17","arxiv_id":"2304.08072","n_code_links":0,"syntology":null},{"paper":"/paper/bitstream-corrupted-jpeg-images-are","slug":"bitstream-corrupted-jpeg-images-are","title":"Bitstream-Corrupted JPEG Images are Restorable: Two-stage Compensation and Alignment Framework for Image Restoration","date":"2023-04-14","arxiv_id":"2304.06976","n_code_links":1,"syntology":{"ran":3,"of":4,"n_ran_checked":3,"n_instrument":0,"unverified":1,"pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 1 honoured, 0 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","official":{"repos":["wenyang001/two-acir"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":"/paper/rethinking-cyclegan-improving-quality-of-gans","slug":"rethinking-cyclegan-improving-quality-of-gans","title":"UVCGAN v2: An Improved Cycle-Consistent GAN for Unpaired Image-to-Image Translation","date":"2023-03-28","arxiv_id":"2303.16280","n_code_links":2,"syntology":null},{"paper":null,"slug":"whole-body-pet-image-denoising-for-reduced","title":"Whole-body PET image denoising for reduced acquisition time","date":"2023-03-28","arxiv_id":"2303.16085","n_code_links":0,"syntology":null},{"paper":"/paper/sat2density-faithful-density-learning-from","slug":"sat2density-faithful-density-learning-from","title":"Sat2Density: Faithful Density Learning from Satellite-Ground Image Pairs","date":"2023-03-26","arxiv_id":"2303.14672","n_code_links":1,"syntology":null},{"paper":null,"slug":"glade-gradient-loss-augmented-degradation","title":"CLADE: Cycle Loss Augmented Degradation Enhancement for Unpaired Super-Resolution of Anisotropic Medical Images","date":"2023-03-21","arxiv_id":"2303.11831","n_code_links":0,"syntology":null},{"paper":null,"slug":"self-film-conditioning-gans-with-self","title":"Self-FiLM: Conditioning GANs with self-supervised representations for bandwidth extension based speaker recognition","date":"2023-03-07","arxiv_id":"2303.03657","n_code_links":0,"syntology":null},{"paper":null,"slug":"hadamard-layer-to-improve-semantic","title":"Hadamard Layer to Improve Semantic Segmentation","date":"2023-02-20","arxiv_id":"2302.10318","n_code_links":0,"syntology":null},{"paper":null,"slug":"local-implicit-neural-representations-for","title":"Local Implicit Neural Representations for Multi-Sequence MRI Translation","date":"2023-02-02","arxiv_id":"2302.01031","n_code_links":0,"syntology":null},{"paper":null,"slug":"standardized-cyclegan-training-for","title":"Standardized CycleGAN training for unsupervised stain adaptation in invasive carcinoma classification for breast histopathology","date":"2023-01-30","arxiv_id":"2301.13128","n_code_links":0,"syntology":null},{"paper":"/paper/improving-statistical-fidelity-for-neural","slug":"improving-statistical-fidelity-for-neural","title":"Improving Statistical Fidelity for Neural Image Compression with Implicit Local Likelihood Models","date":"2023-01-26","arxiv_id":"2301.11189","n_code_links":1,"syntology":null},{"paper":null,"slug":"multi-domain-stain-normalization-for-digital","title":"Multi-domain stain normalization for digital pathology: A cycle-consistent adversarial network for whole slide images","date":"2023-01-23","arxiv_id":"2301.09431","n_code_links":0,"syntology":null},{"paper":null,"slug":"unpaired-image-to-image-translation-with-1","title":"Unpaired Image-to-Image Translation with Limited Data to Reveal Subtle Phenotypes","date":"2023-01-21","arxiv_id":"2302.08503","n_code_links":0,"syntology":null},{"paper":"/paper/using-cyclegans-to-generate-realistic-stem","slug":"using-cyclegans-to-generate-realistic-stem","title":"Leveraging generative adversarial networks to create realistic scanning transmission electron microscopy images","date":"2023-01-18","arxiv_id":"2301.07743","n_code_links":1,"syntology":null},{"paper":"/paper/discriminator-cooperated-feature-map","slug":"discriminator-cooperated-feature-map","title":"Discriminator-Cooperated Feature Map Distillation for GAN Compression","date":"2022-12-29","arxiv_id":"2212.14169","n_code_links":1,"syntology":null},{"paper":null,"slug":"unpaired-overwater-image-defogging-using","title":"Unpaired Overwater Image Defogging Using Prior Map Guided CycleGAN","date":"2022-12-23","arxiv_id":"2212.12116","n_code_links":0,"syntology":null},{"paper":"/paper/jamdani-motif-generation-using-conditional","slug":"jamdani-motif-generation-using-conditional","title":"Jamdani Motif Generation using Conditional GAN","date":"2022-12-22","arxiv_id":"2212.11824","n_code_links":1,"syntology":null},{"paper":"/paper/exploring-content-relationships-for","slug":"exploring-content-relationships-for","title":"Exploring Content Relationships for Distilling Efficient GANs","date":"2022-12-21","arxiv_id":"2212.11091","n_code_links":1,"syntology":null},{"paper":"/paper/on-the-applicability-of-synthetic-data-for-re","slug":"on-the-applicability-of-synthetic-data-for-re","title":"On the Applicability of Synthetic Data for Re-Identification","date":"2022-12-20","arxiv_id":"2212.10105","n_code_links":1,"syntology":null},{"paper":"/paper/efficient-visual-computing-with-camera-raw","slug":"efficient-visual-computing-with-camera-raw","title":"Efficient Visual Computing with Camera RAW Snapshots","date":"2022-12-15","arxiv_id":"2212.07778","n_code_links":1,"syntology":null},{"paper":null,"slug":"gamma-generative-augmentation-for-attentive","title":"GAMMA: Generative Augmentation for Attentive Marine Debris Detection","date":"2022-12-07","arxiv_id":"2212.03759","n_code_links":0,"syntology":null},{"paper":"/paper/single-slice-thigh-ct-muscle-group","slug":"single-slice-thigh-ct-muscle-group","title":"Single Slice Thigh CT Muscle Group Segmentation with Domain Adaptation and Self-Training","date":"2022-11-30","arxiv_id":"2212.00059","n_code_links":1,"syntology":null},{"paper":null,"slug":"artifact-removal-in-histopathology-images","title":"Artifact Removal in Histopathology Images","date":"2022-11-29","arxiv_id":"2211.16161","n_code_links":0,"syntology":null},{"paper":null,"slug":"an-unpaired-cross-modality-segmentation","title":"An Unpaired Cross-modality Segmentation Framework Using Data Augmentation and Hybrid Convolutional Networks for Segmenting Vestibular Schwannoma and Cochlea","date":"2022-11-28","arxiv_id":"2211.14986","n_code_links":0,"syntology":null},{"paper":null,"slug":"sgce-font-skeleton-guided-channel-expansion","title":"SGCE-Font: Skeleton Guided Channel Expansion for Chinese Font Generation","date":"2022-11-26","arxiv_id":"2211.14475","n_code_links":0,"syntology":null},{"paper":"/paper/dynamic-pix2pix-noise-injected-cgan-for","slug":"dynamic-pix2pix-noise-injected-cgan-for","title":"Dynamic-Pix2Pix: Noise Injected cGAN for Modeling Input and Target Domain Joint Distributions with Limited Training Data","date":"2022-11-15","arxiv_id":"2211.08570","n_code_links":1,"syntology":null},{"paper":null,"slug":"disentangled-uncertainty-and-out-of","title":"Disentangled Uncertainty and Out of Distribution Detection in Medical Generative Models","date":"2022-11-11","arxiv_id":"2211.06250","n_code_links":0,"syntology":null},{"paper":null,"slug":"strokegan-few-shot-semi-supervised-chinese","title":"StrokeGAN+: Few-Shot Semi-Supervised Chinese Font Generation with Stroke Encoding","date":"2022-11-11","arxiv_id":"2211.06198","n_code_links":0,"syntology":null},{"paper":null,"slug":"h-e-stain-normalization-using-u-net","title":"H&E Stain Normalization using U-Net","date":"2022-11-10","arxiv_id":"2211.05420","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-diffeomorphic-flow-based-variational","title":"A Diffeomorphic Flow-based Variational Framework for Multi-speaker Emotion Conversion","date":"2022-11-09","arxiv_id":"2211.05071","n_code_links":0,"syntology":null},{"paper":"/paper/dc-cyclegan-bidirectional-ct-to-mr-synthesis","slug":"dc-cyclegan-bidirectional-ct-to-mr-synthesis","title":"DC-cycleGAN: Bidirectional CT-to-MR Synthesis from Unpaired Data","date":"2022-11-02","arxiv_id":"2211.01293","n_code_links":1,"syntology":null},{"paper":null,"slug":"digital-twins-of-physical-printing-imaging","title":"Digital twins of physical printing-imaging channel","date":"2022-10-28","arxiv_id":"2210.17420","n_code_links":0,"syntology":null},{"paper":"/paper/nonparallel-high-quality-audio-super","slug":"nonparallel-high-quality-audio-super","title":"Nonparallel High-Quality Audio Super Resolution with Domain Adaptation and Resampling CycleGANs","date":"2022-10-28","arxiv_id":"2210.15887","n_code_links":1,"syntology":null},{"paper":null,"slug":"improving-semi-supervised-end-to-end","title":"Improving Semi-supervised End-to-end Automatic Speech Recognition using CycleGAN and Inter-domain Losses","date":"2022-10-20","arxiv_id":"2210.11642","n_code_links":0,"syntology":null},{"paper":null,"slug":"wide-range-mri-artifact-removal-with","title":"Wide Range MRI Artifact Removal with Transformers","date":"2022-10-14","arxiv_id":"2210.07976","n_code_links":0,"syntology":null},{"paper":null,"slug":"anatomically-constrained-ct-image-translation","title":"Anatomically constrained CT image translation for heterogeneous blood vessel segmentation","date":"2022-10-04","arxiv_id":"2210.01713","n_code_links":0,"syntology":null},{"paper":null,"slug":"cyclegan-network-for-sheet-metal-welding","title":"Cyclegan Network for Sheet Metal Welding Drawing Translation","date":"2022-09-28","arxiv_id":"2209.14106","n_code_links":0,"syntology":null},{"paper":null,"slug":"vector-quantized-semantic-communication","title":"Vector Quantized Semantic Communication System","date":"2022-09-23","arxiv_id":"2209.11519","n_code_links":0,"syntology":null}],"record_sha256":"e6bfff8f30c0b825e242fa57b51da649c1b3635aab33bb12667776857e16ecb8","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}