{"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-generation/papers/66","list_of":"/task/image-generation","task":"Image Generation","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":66,"pages_in_order":67,"rows_per_page":100,"rows":[6501,6600],"of":6689,"counts":{"archive_papers_tagged":6689,"with_a_code_link":3102,"where_syntology_ran_a_sample":1223,"not_listed_spam_title":0,"listed":6689,"listed_where_code_ran":1223,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":1063,"every_run_a_failure_of_syntologys_instrument":160,"listed_with_a_run_with_no_instrument_failure":1063,"listed_every_run_a_failure_of_syntologys_instrument":160,"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-generation","prev":"/task/image-generation/papers/65","next":"/task/image-generation/papers/67","papers":[{"url":null,"slug":"students-t-generative-adversarial-networks","title":"Student's t-Generative Adversarial Networks","date":"2018-11-06","arxiv_id":"1811.02132","repositories_listed":0,"syntology":null},{"url":null,"slug":"fast-face-image-synthesis-with-minimal","title":"Fast Face Image Synthesis with Minimal Training","date":"2018-11-05","arxiv_id":"1811.01474","repositories_listed":0,"syntology":null},{"url":null,"slug":"isa4ml-training-data-unaware-imperceptible","title":"TrISec: Training Data-Unaware Imperceptible Security Attacks on Deep Neural Networks","date":"2018-11-02","arxiv_id":"1811.01031","repositories_listed":0,"syntology":null},{"url":null,"slug":"evaluating-textual-representations-through","title":"Evaluating Textual Representations through Image Generation","date":"2018-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-cnn-training-using-disentanglement","title":"Improving CNN Training using Disentanglement for Liver Lesion Classification in CT","date":"2018-11-01","arxiv_id":"1811.00501","repositories_listed":0,"syntology":null},{"url":null,"slug":"waveform-generation-for-text-to-speech","title":"Waveform generation for text-to-speech synthesis using pitch-synchronous multi-scale generative adversarial networks","date":"2018-10-30","arxiv_id":"1810.12598","repositories_listed":0,"syntology":null},{"url":null,"slug":"soft-gated-warping-gan-for-pose-guided-person","title":"Soft-Gated Warping-GAN for Pose-Guided Person Image Synthesis","date":"2018-10-27","arxiv_id":"1810.11610","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-adversarial-learning-approach-to-medical","title":"An Adversarial Learning Approach to Medical Image Synthesis for Lesion Detection","date":"2018-10-25","arxiv_id":"1810.10850","repositories_listed":0,"syntology":null},{"url":null,"slug":"variational-learning-across-domains-with-1","title":"Variational learning across domains with triplet information","date":"2018-10-22","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"mscgan-multi-scale-conditional-generative","title":"MsCGAN: Multi-scale Conditional Generative Adversarial Networks for Person Image Generation","date":"2018-10-19","arxiv_id":"1810.08534","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-case-for-object-compositionality-in-deep","title":"Investigating Object Compositionality in Generative Adversarial Networks","date":"2018-10-17","arxiv_id":"1810.10340","repositories_listed":0,"syntology":null},{"url":null,"slug":"skip-thought-gan-generating-text-through","title":"Skip-Thought GAN: Generating Text through Adversarial Training using Skip-Thought Vectors","date":"2018-10-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"canvasgan-a-simple-baseline-for-text-to-image","title":"CanvasGAN: A simple baseline for text to image generation by incrementally patching a canvas","date":"2018-10-05","arxiv_id":"1810.02833","repositories_listed":0,"syntology":null},{"url":null,"slug":"salsa-text-self-attentive-latent-space-based","title":"SALSA-TEXT : self attentive latent space based adversarial text generation","date":"2018-09-28","arxiv_id":"1809.11155","repositories_listed":0,"syntology":null},{"url":null,"slug":"adversarial-audio-super-resolution-with","title":"Adversarial Audio Super-Resolution with Unsupervised Feature Losses","date":"2018-09-27","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"autoloss-learning-discrete-schedule-for","title":"AutoLoss: Learning Discrete Schedule for Alternate Optimization","date":"2018-09-27","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-adversarial-forward-model","title":"DEEP ADVERSARIAL FORWARD MODEL","date":"2018-09-27","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"flow-based-network-traffic-generation-using","title":"Flow-based Network Traffic Generation using Generative Adversarial Networks","date":"2018-09-27","arxiv_id":"1810.07795","repositories_listed":0,"syntology":null},{"url":null,"slug":"generating-images-from-sounds-using","title":"Generating Images from Sounds Using Multimodal Features and GANs","date":"2018-09-27","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-neural-random-fields-with-inclusive-1","title":"Learning Neural Random Fields with Inclusive Auxiliary Generators","date":"2018-09-27","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"pa-gan-improving-gan-training-by-progressive-1","title":"PA-GAN: Improving GAN Training by Progressive Augmentation","date":"2018-09-27","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"semantically-invariant-text-to-image","title":"Semantically Invariant Text-to-Image Generation","date":"2018-09-27","arxiv_id":"1809.10274","repositories_listed":0,"syntology":null},{"url":null,"slug":"topicgan-unsupervised-text-generation-from","title":"TopicGAN: Unsupervised Text Generation from Explainable Latent Topics","date":"2018-09-27","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"unsupervised-person-image-synthesis-in","title":"Unsupervised Person Image Synthesis in Arbitrary Poses","date":"2018-09-27","arxiv_id":"1809.10280","repositories_listed":0,"syntology":null},{"url":null,"slug":"vector-learning-for-cross-domain","title":"Vector Learning for Cross Domain Representations","date":"2018-09-27","arxiv_id":"1809.10312","repositories_listed":0,"syntology":null},{"url":null,"slug":"c4synth-cross-caption-cycle-consistent-text","title":"C4Synth: Cross-Caption Cycle-Consistent Text-to-Image Synthesis","date":"2018-09-20","arxiv_id":"1809.10238","repositories_listed":0,"syntology":null},{"url":null,"slug":"pose-estimation-for-non-cooperative","title":"Pose Estimation for Non-Cooperative Spacecraft Rendezvous Using Convolutional Neural Networks","date":"2018-09-19","arxiv_id":"1809.07238","repositories_listed":0,"syntology":null},{"url":null,"slug":"feature2mass-visual-feature-processing-in","title":"Feature2Mass: Visual Feature Processing in Latent Space for Realistic Labeled Mass Generation","date":"2018-09-17","arxiv_id":"1809.06147","repositories_listed":0,"syntology":null},{"url":null,"slug":"geometric-image-synthesis","title":"Geometric Image Synthesis","date":"2018-09-12","arxiv_id":"1809.04696","repositories_listed":0,"syntology":null},{"url":null,"slug":"unpaired-brain-mr-to-ct-synthesis-using-a","title":"Unpaired Brain MR-to-CT Synthesis using a Structure-Constrained CycleGAN","date":"2018-09-12","arxiv_id":"1809.04536","repositories_listed":0,"syntology":null},{"url":null,"slug":"neural-animation-and-reenactment-of-human","title":"Neural Rendering and Reenactment of Human Actor Videos","date":"2018-09-11","arxiv_id":"1809.03658","repositories_listed":0,"syntology":null},{"url":null,"slug":"open-set-learning-with-counterfactual-images","title":"Open Set Learning with Counterfactual Images","date":"2018-09-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"treegan-syntax-aware-sequence-generation-with","title":"TreeGAN: Syntax-Aware Sequence Generation with Generative Adversarial Networks","date":"2018-08-22","arxiv_id":"1808.07582","repositories_listed":0,"syntology":null},{"url":null,"slug":"text-to-image-synthesis-via-symmetrical","title":"Text-to-image Synthesis via Symmetrical Distillation Networks","date":"2018-08-21","arxiv_id":"1808.06801","repositories_listed":0,"syntology":null},{"url":null,"slug":"gridface-face-rectification-via-learning","title":"GridFace: Face Rectification via Learning Local Homography Transformations","date":"2018-08-19","arxiv_id":"1808.06210","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-audio-to-scene-image-synthesis-using","title":"Towards Audio to Scene Image Synthesis using Generative Adversarial Network","date":"2018-08-13","arxiv_id":"1808.04108","repositories_listed":0,"syntology":null},{"url":null,"slug":"unsupervised-learning-for-cross-domain","title":"Unsupervised learning for cross-domain medical image synthesis using deformation invariant cycle consistency networks","date":"2018-08-12","arxiv_id":"1808.03944","repositories_listed":0,"syntology":null},{"url":null,"slug":"medical-image-synthesis-for-data-augmentation","title":"Medical Image Synthesis for Data Augmentation and Anonymization using Generative Adversarial Networks","date":"2018-07-26","arxiv_id":"1807.10225","repositories_listed":0,"syntology":null},{"url":null,"slug":"improved-training-with-curriculum-gans","title":"Improved Training with Curriculum GANs","date":"2018-07-24","arxiv_id":"1807.09295","repositories_listed":0,"syntology":null},{"url":null,"slug":"generic-camera-attribute-control-using","title":"Generic Camera Attribute Control using Bayesian Optimization","date":"2018-07-21","arxiv_id":"1807.10596","repositories_listed":0,"syntology":null},{"url":null,"slug":"generative-adversarial-networks-for-mr-ct","title":"Generative Adversarial Networks for MR-CT Deformable Image Registration","date":"2018-07-19","arxiv_id":"1807.07349","repositories_listed":0,"syntology":null},{"url":null,"slug":"variational-capsules-for-image-analysis-and","title":"Variational Capsules for Image Analysis and Synthesis","date":"2018-07-11","arxiv_id":"1807.04099","repositories_listed":0,"syntology":null},{"url":null,"slug":"high-resolution-mammogram-synthesis-using","title":"High-Resolution Mammogram Synthesis using Progressive Generative Adversarial Networks","date":"2018-07-09","arxiv_id":"1807.03401","repositories_listed":0,"syntology":null},{"url":null,"slug":"vehicle-image-generation-going-well-with-the","title":"Vehicle Image Generation Going Well with The Surroundings","date":"2018-07-09","arxiv_id":"1807.02925","repositories_listed":0,"syntology":null},{"url":null,"slug":"verisimilar-image-synthesis-for-accurate","title":"Verisimilar Image Synthesis for Accurate Detection and Recognition of Texts in Scenes","date":"2018-07-09","arxiv_id":"1807.03021","repositories_listed":0,"syntology":null},{"url":null,"slug":"synnet-structure-preserving-fully","title":"SynNet: Structure-Preserving Fully Convolutional Networks for Medical Image Synthesis","date":"2018-06-29","arxiv_id":"1806.11475","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-generative-models-with-learnable","title":"Deep Generative Models with Learnable Knowledge Constraints","date":"2018-06-26","arxiv_id":"1806.09764","repositories_listed":0,"syntology":null},{"url":null,"slug":"variational-learning-across-domains-with","title":"Variational learning across domains with triplet information","date":"2018-06-22","arxiv_id":"1806.08672","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-neural-painter-multi-turn-image","title":"The Neural Painter: Multi-Turn Image Generation","date":"2018-06-16","arxiv_id":"1806.06183","repositories_listed":0,"syntology":null},{"url":null,"slug":"generative-adversarial-network-architectures","title":"Generative Adversarial Network Architectures For Image Synthesis Using Capsule Networks","date":"2018-06-11","arxiv_id":"1806.03796","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-hierarchical-generative-model-for-eye-image","title":"A Hierarchical Generative Model for Eye Image Synthesis and Eye Gaze Estimation","date":"2018-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"human-appearance-transfer","title":"Human Appearance Transfer","date":"2018-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"joint-pose-and-expression-modeling-for-facial","title":"Joint Pose and Expression Modeling for Facial Expression Recognition","date":"2018-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-task-adversarial-network-for","title":"Multi-Task Adversarial Network for Disentangled Feature Learning","date":"2018-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"multistage-adversarial-losses-for-pose-based","title":"Multistage Adversarial Losses for Pose-Based Human Image Synthesis","date":"2018-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"generative-adversarial-image-synthesis-with","title":"Generative Adversarial Image Synthesis with Decision Tree Latent Controller","date":"2018-05-27","arxiv_id":"1805.10603","repositories_listed":0,"syntology":null},{"url":null,"slug":"cross-domain-image-generation-through-latent","title":"Cross Domain Image Generation through Latent Space Exploration with Adversarial Loss","date":"2018-05-24","arxiv_id":"1805.10130","repositories_listed":0,"syntology":null},{"url":null,"slug":"anime-style-space-exploration-using-metric","title":"Anime Style Space Exploration Using Metric Learning and Generative Adversarial Networks","date":"2018-05-21","arxiv_id":"1805.07997","repositories_listed":0,"syntology":null},{"url":null,"slug":"turbo-learning-for-captionbot-and-drawingbot","title":"Turbo Learning for Captionbot and Drawingbot","date":"2018-05-21","arxiv_id":"1805.08170","repositories_listed":0,"syntology":null},{"url":null,"slug":"xogan-one-to-many-unsupervised-image-to-image","title":"XOGAN: One-to-Many Unsupervised Image-to-Image Translation","date":"2018-05-18","arxiv_id":"1805.07277","repositories_listed":0,"syntology":null},{"url":null,"slug":"normal-similarity-network-for-generative","title":"Normal Similarity Network for Generative Modelling","date":"2018-05-14","arxiv_id":"1805.05269","repositories_listed":0,"syntology":null},{"url":null,"slug":"high-resolution-medical-image-synthesis-using","title":"High-resolution medical image synthesis using progressively grown generative adversarial networks","date":"2018-05-08","arxiv_id":"1805.03144","repositories_listed":0,"syntology":null},{"url":null,"slug":"regan-relaxbarinforce-based-sequence","title":"ReGAN: RE[LAX|BAR|INFORCE] based Sequence Generation using GANs","date":"2018-05-08","arxiv_id":"1805.02788","repositories_listed":0,"syntology":null},{"url":null,"slug":"megan-mixture-of-experts-of-generative","title":"MEGAN: Mixture of Experts of Generative Adversarial Networks for Multimodal Image Generation","date":"2018-05-07","arxiv_id":"1805.02481","repositories_listed":0,"syntology":null},{"url":null,"slug":"fast-converging-conditional-generative","title":"Fast-converging Conditional Generative Adversarial Networks for Image Synthesis","date":"2018-05-05","arxiv_id":"1805.01972","repositories_listed":0,"syntology":null},{"url":null,"slug":"text-to-image-synthesis-using-generative","title":"Text to Image Synthesis Using Generative Adversarial Networks","date":"2018-05-02","arxiv_id":"1805.00676","repositories_listed":0,"syntology":null},{"url":null,"slug":"polish-corpus-of-annotated-descriptions-of","title":"Polish Corpus of Annotated Descriptions of Images","date":"2018-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"wikiart-emotions-an-annotated-dataset-of","title":"WikiArt Emotions: An Annotated Dataset of Emotions Evoked by Art","date":"2018-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"a-hybrid-model-for-identity-obfuscation-by","title":"A Hybrid Model for Identity Obfuscation by Face Replacement","date":"2018-04-13","arxiv_id":"1804.04779","repositories_listed":0,"syntology":null},{"url":null,"slug":"generative-adversarial-training-for-mra-image","title":"Generative Adversarial Training for MRA Image Synthesis Using Multi-Contrast MRI","date":"2018-04-12","arxiv_id":"1804.04366","repositories_listed":0,"syntology":null},{"url":null,"slug":"melanogans-high-resolution-skin-lesion","title":"MelanoGANs: High Resolution Skin Lesion Synthesis with GANs","date":"2018-04-12","arxiv_id":"1804.04338","repositories_listed":0,"syntology":null},{"url":null,"slug":"projection-image-to-image-translation-in","title":"Projection image-to-image translation in hybrid X-ray/MR imaging","date":"2018-04-11","arxiv_id":"1804.03955","repositories_listed":0,"syntology":null},{"url":null,"slug":"ranking-cgans-subjective-control-over","title":"Ranking CGANs: Subjective Control over Semantic Image Attributes","date":"2018-04-11","arxiv_id":"1804.04082","repositories_listed":0,"syntology":null},{"url":null,"slug":"view-extrapolation-of-human-body-from-a","title":"View Extrapolation of Human Body from a Single Image","date":"2018-04-11","arxiv_id":"1804.04213","repositories_listed":0,"syntology":null},{"url":null,"slug":"language-modeling-with-generative","title":"Language Modeling with Generative AdversarialNetworks","date":"2018-04-08","arxiv_id":"1804.02617","repositories_listed":0,"syntology":null},{"url":null,"slug":"correlated-discrete-data-generation-using","title":"Correlated discrete data generation using adversarial training","date":"2018-04-03","arxiv_id":"1804.00925","repositories_listed":0,"syntology":null},{"url":null,"slug":"guide-me-interacting-with-deep-networks","title":"Guide Me: Interacting with Deep Networks","date":"2018-03-30","arxiv_id":"1803.11544","repositories_listed":0,"syntology":null},{"url":null,"slug":"3d-consistent-biventricular-myocardial","title":"3D Consistent Biventricular Myocardial Segmentation Using Deep Learning for Mesh Generation","date":"2018-03-29","arxiv_id":"1803.11080","repositories_listed":0,"syntology":null},{"url":null,"slug":"image-generation-and-translation-with","title":"Image Generation and Translation with Disentangled Representations","date":"2018-03-28","arxiv_id":"1803.10567","repositories_listed":0,"syntology":null},{"url":null,"slug":"vgan-based-image-representation-learning-for","title":"VGAN-Based Image Representation Learning for Privacy-Preserving Facial Expression Recognition","date":"2018-03-19","arxiv_id":"1803.07100","repositories_listed":0,"syntology":null},{"url":null,"slug":"cross-modality-image-synthesis-from-unpaired","title":"Cross-modality image synthesis from unpaired data using CycleGAN: Effects of gradient consistency loss and training data size","date":"2018-03-18","arxiv_id":"1803.06629","repositories_listed":0,"syntology":null},{"url":null,"slug":"line-artist-a-multiple-style-sketch-to","title":"Line Artist: A Multiple Style Sketch to Painting Synthesis Scheme","date":"2018-03-18","arxiv_id":"1803.06647","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-introduction-to-image-synthesis-with","title":"An Introduction to Image Synthesis with Generative Adversarial Nets","date":"2018-03-12","arxiv_id":"1803.04469","repositories_listed":0,"syntology":null},{"url":null,"slug":"translating-and-segmenting-multimodal-medical","title":"Translating and Segmenting Multimodal Medical Volumes with Cycle- and Shape-Consistency Generative Adversarial Network","date":"2018-02-27","arxiv_id":"1802.09655","repositories_listed":0,"syntology":null},{"url":null,"slug":"constrained-image-generation-using-binarized","title":"Constrained Image Generation Using Binarized Neural Networks with Decision Procedures","date":"2018-02-24","arxiv_id":"1802.08795","repositories_listed":0,"syntology":null},{"url":null,"slug":"interactive-image-manipulation-with-natural","title":"Interactive Image Manipulation with Natural Language Instruction Commands","date":"2018-02-23","arxiv_id":"1802.08645","repositories_listed":0,"syntology":null},{"url":"/paper/chatpainter-improving-text-to-image","slug":"chatpainter-improving-text-to-image","title":"ChatPainter: Improving Text to Image Generation using Dialogue","date":"2018-02-22","arxiv_id":"1802.08216","repositories_listed":0,"syntology":null},{"url":null,"slug":"magnifyme-aiding-cross-resolution-face","title":"MagnifyMe: Aiding Cross Resolution Face Recognition via Identity Aware Synthesis","date":"2018-02-22","arxiv_id":"1802.08057","repositories_listed":0,"syntology":null},{"url":null,"slug":"conditional-adversarial-synthesis-of-3d","title":"Conditional Adversarial Synthesis of 3D Facial Action Units","date":"2018-02-21","arxiv_id":"1802.07421","repositories_listed":0,"syntology":null},{"url":null,"slug":"load-balanced-gans-for-multi-view-face-image","title":"Load Balanced GANs for Multi-view Face Image Synthesis","date":"2018-02-21","arxiv_id":"1802.07447","repositories_listed":0,"syntology":null},{"url":"/paper/image-transformer","slug":"image-transformer","title":"Image Transformer","date":"2018-02-15","arxiv_id":"1802.05751","repositories_listed":0,"syntology":null},{"url":null,"slug":"dvae-discrete-variational-autoencoders-with-1","title":"DVAE++: Discrete Variational Autoencoders with Overlapping Transformations","date":"2018-02-14","arxiv_id":"1802.04920","repositories_listed":0,"syntology":null},{"url":null,"slug":"combinets-creativity-via-recombination-of","title":"Combinets: Creativity via Recombination of Neural Networks","date":"2018-02-10","arxiv_id":"1802.03605","repositories_listed":0,"syntology":null},{"url":null,"slug":"improved-training-of-generative-adversarial","title":"Improved Training of Generative Adversarial Networks Using Representative Features","date":"2018-01-28","arxiv_id":"1801.09195","repositories_listed":0,"syntology":null},{"url":null,"slug":"three-dimensional-fluorescence-microscopy","title":"Three Dimensional Fluorescence Microscopy Image Synthesis and Segmentation","date":"2018-01-22","arxiv_id":"1801.07198","repositories_listed":0,"syntology":null},{"url":null,"slug":"semi-supervised-fusedgan-for-conditional","title":"Semi-supervised FusedGAN for Conditional Image Generation","date":"2018-01-17","arxiv_id":"1801.05551","repositories_listed":0,"syntology":null},{"url":null,"slug":"inferring-semantic-layout-for-hierarchical","title":"Inferring Semantic Layout for Hierarchical Text-to-Image Synthesis","date":"2018-01-16","arxiv_id":"1801.05091","repositories_listed":0,"syntology":null},{"url":null,"slug":"instance-map-based-image-synthesis-with-a","title":"Instance Map based Image Synthesis with a Denoising Generative Adversarial Network","date":"2018-01-10","arxiv_id":"1801.03252","repositories_listed":0,"syntology":null},{"url":null,"slug":"generative-sensing-transforming-unreliable","title":"Generative Sensing: Transforming Unreliable Sensor Data for Reliable Recognition","date":"2018-01-08","arxiv_id":"1801.02684","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-implicit-brain-mri-manifolds-with","title":"Learning Implicit Brain MRI Manifolds with Deep Learning","date":"2018-01-05","arxiv_id":"1801.01847","repositories_listed":0,"syntology":null}],"record_sha256":"39323bdd92cce41cc8f81d00c771bdb9744bf2853c656be15ab53f45db8c1f84","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}