{"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/56","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":56,"pages_in_order":67,"rows_per_page":100,"rows":[5501,5600],"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/55","next":"/task/image-generation/papers/57","papers":[{"url":null,"slug":"exploring-transformer-backbones-for-image","title":"Exploring Transformer Backbones for Image Diffusion Models","date":"2022-12-27","arxiv_id":"2212.14678","repositories_listed":0,"syntology":null},{"url":null,"slug":"application-of-unsupervised-domain-adaptation","title":"Application of Unsupervised Domain Adaptation for Structural MRI Analysis","date":"2022-12-26","arxiv_id":"2212.12986","repositories_listed":0,"syntology":null},{"url":null,"slug":"do-dall-e-and-flamingo-understand-each-other","title":"Do DALL-E and Flamingo Understand Each Other?","date":"2022-12-23","arxiv_id":"2212.12249","repositories_listed":0,"syntology":null},{"url":null,"slug":"discoscene-spatially-disentangled-generative","title":"DisCoScene: Spatially Disentangled Generative Radiance Fields for Controllable 3D-aware Scene Synthesis","date":"2022-12-22","arxiv_id":"2212.11984","repositories_listed":0,"syntology":null},{"url":null,"slug":"conditioned-generative-transformers-for","title":"Unified Framework for Histopathology Image Augmentation and Classification via Generative Models","date":"2022-12-20","arxiv_id":"2212.09977","repositories_listed":0,"syntology":null},{"url":null,"slug":"local-differential-privacy-image-generation","title":"Local Differential Privacy Image Generation Using Flow-based Deep Generative Models","date":"2022-12-20","arxiv_id":"2212.10688","repositories_listed":0,"syntology":null},{"url":null,"slug":"metaclue-towards-comprehensive-visual","title":"MetaCLUE: Towards Comprehensive Visual Metaphors Research","date":"2022-12-19","arxiv_id":"2212.09898","repositories_listed":0,"syntology":null},{"url":null,"slug":"speed-up-the-inference-of-diffusion-models","title":"Speed up the inference of diffusion models via shortcut MCMC sampling","date":"2022-12-18","arxiv_id":"2301.01206","repositories_listed":0,"syntology":null},{"url":null,"slug":"human-image-generation-a-comprehensive-survey","title":"Human Image Generation: A Comprehensive Survey","date":"2022-12-17","arxiv_id":"2212.08896","repositories_listed":0,"syntology":null},{"url":null,"slug":"fake-it-till-you-make-it-learning-s-from-a","title":"Fake it till you make it: Learning transferable representations from synthetic ImageNet clones","date":"2022-12-16","arxiv_id":"2212.08420","repositories_listed":0,"syntology":null},{"url":null,"slug":"image-compression-with-product-quantized","title":"Image Compression with Product Quantized Masked Image Modeling","date":"2022-12-14","arxiv_id":"2212.07372","repositories_listed":0,"syntology":null},{"url":null,"slug":"spirit-diffusion-spirit-driven-score-based","title":"SPIRiT-Diffusion: SPIRiT-driven Score-Based Generative Modeling for Vessel Wall imaging","date":"2022-12-14","arxiv_id":"2212.11274","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-infinite-index-information-retrieval-on","title":"The Infinite Index: Information Retrieval on Generative Text-To-Image Models","date":"2022-12-14","arxiv_id":"2212.07476","repositories_listed":0,"syntology":null},{"url":null,"slug":"haca3-a-unified-approach-for-multi-site-mr","title":"HACA3: A Unified Approach for Multi-site MR Image Harmonization","date":"2022-12-12","arxiv_id":"2212.06065","repositories_listed":0,"syntology":null},{"url":null,"slug":"album-cover-art-image-generation-with","title":"Album cover art image generation with Generative Adversarial Networks","date":"2022-12-09","arxiv_id":"2212.04844","repositories_listed":0,"syntology":null},{"url":null,"slug":"judge-localize-and-edit-ensuring-visual","title":"Ensuring Visual Commonsense Morality for Text-to-Image Generation","date":"2022-12-07","arxiv_id":"2212.03507","repositories_listed":0,"syntology":null},{"url":null,"slug":"adir-adaptive-diffusion-for-image","title":"ADIR: Adaptive Diffusion for Image Reconstruction","date":"2022-12-06","arxiv_id":"2212.03221","repositories_listed":0,"syntology":null},{"url":null,"slug":"m-vader-a-model-for-diffusion-with-multimodal","title":"M-VADER: A Model for Diffusion with Multimodal Context","date":"2022-12-06","arxiv_id":"2212.02936","repositories_listed":0,"syntology":null},{"url":null,"slug":"rana-relightable-articulated-neural-avatars","title":"RANA: Relightable Articulated Neural Avatars","date":"2022-12-06","arxiv_id":"2212.03237","repositories_listed":0,"syntology":null},{"url":null,"slug":"rethinking-the-objectives-of-vector-quantized","title":"Rethinking the Objectives of Vector-Quantized Tokenizers for Image Synthesis","date":"2022-12-06","arxiv_id":"2212.03185","repositories_listed":0,"syntology":null},{"url":null,"slug":"audio-latent-space-cartography","title":"Audio Latent Space Cartography","date":"2022-12-05","arxiv_id":"2212.02610","repositories_listed":0,"syntology":null},{"url":null,"slug":"mousegan-unsupervised-disentanglement-and","title":"MouseGAN++: Unsupervised Disentanglement and Contrastive Representation for Multiple MRI Modalities Synthesis and Structural Segmentation of Mouse Brain","date":"2022-12-04","arxiv_id":"2212.01825","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-domain-specific-perceptual-metric-via","title":"A Domain-specific Perceptual Metric via Contrastive Self-supervised Representation: Applications on Natural and Medical Images","date":"2022-12-03","arxiv_id":"2212.01577","repositories_listed":0,"syntology":null},{"url":null,"slug":"discovering-class-specific-gan-controls-for","title":"Discovering Class-Specific GAN Controls for Semantic Image Synthesis","date":"2022-12-02","arxiv_id":"2212.01455","repositories_listed":0,"syntology":null},{"url":null,"slug":"3d-ldm-neural-implicit-3d-shape-generation","title":"3D-LDM: Neural Implicit 3D Shape Generation with Latent Diffusion Models","date":"2022-12-01","arxiv_id":"2212.00842","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-neural-network-techniques-for-monaural","title":"Deep neural network techniques for monaural speech enhancement: state of the art analysis","date":"2022-12-01","arxiv_id":"2212.00369","repositories_listed":0,"syntology":null},{"url":null,"slug":"sparsefusion-distilling-view-conditioned","title":"SparseFusion: Distilling View-conditioned Diffusion for 3D Reconstruction","date":"2022-12-01","arxiv_id":"2212.00792","repositories_listed":0,"syntology":null},{"url":null,"slug":"weakly-supervised-annotations-for-multi-modal","title":"Weakly Supervised Annotations for Multi-modal Greeting Cards Dataset","date":"2022-12-01","arxiv_id":"2212.00847","repositories_listed":0,"syntology":null},{"url":null,"slug":"3d-neural-field-generation-using-triplane","title":"3D Neural Field Generation using Triplane Diffusion","date":"2022-11-30","arxiv_id":"2211.16677","repositories_listed":0,"syntology":null},{"url":null,"slug":"dr-3d-adapting-3d-gans-to-artistic-drawings","title":"Dr.3D: Adapting 3D GANs to Artistic Drawings","date":"2022-11-30","arxiv_id":"2211.16798","repositories_listed":0,"syntology":null},{"url":null,"slug":"extracting-semantic-knowledge-from-gans-with","title":"Extracting Semantic Knowledge from GANs with Unsupervised Learning","date":"2022-11-30","arxiv_id":"2211.16710","repositories_listed":0,"syntology":null},{"url":null,"slug":"high-fidelity-guided-image-synthesis-with","title":"High-Fidelity Guided Image Synthesis with Latent Diffusion Models","date":"2022-11-30","arxiv_id":"2211.17084","repositories_listed":0,"syntology":null},{"url":null,"slug":"dimensionality-varying-diffusion-process","title":"Dimensionality-Varying Diffusion Process","date":"2022-11-29","arxiv_id":"2211.16032","repositories_listed":0,"syntology":null},{"url":null,"slug":"clip2gan-towards-bridging-text-with-the","title":"CLIP2GAN: Towards Bridging Text with the Latent Space of GANs","date":"2022-11-28","arxiv_id":"2211.15045","repositories_listed":0,"syntology":null},{"url":null,"slug":"conditional-progressive-generative","title":"Conditional Progressive Generative Adversarial Network for satellite image generation","date":"2022-11-28","arxiv_id":"2211.15303","repositories_listed":0,"syntology":null},{"url":null,"slug":"hand-object-interaction-image-generation","title":"Hand-Object Interaction Image Generation","date":"2022-11-28","arxiv_id":"2211.15663","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-myth-of-culturally-agnostic-ai-models","title":"The Myth of Culturally Agnostic AI Models","date":"2022-11-28","arxiv_id":"2211.15271","repositories_listed":0,"syntology":null},{"url":null,"slug":"using-a-conditional-generative-adversarial","title":"Using a Conditional Generative Adversarial Network to Control the Statistical Characteristics of Generated Images for IACT Data Analysis","date":"2022-11-28","arxiv_id":"2211.15807","repositories_listed":0,"syntology":null},{"url":null,"slug":"diffusion-probabilistic-model-made-slim","title":"Diffusion Probabilistic Model Made Slim","date":"2022-11-27","arxiv_id":"2211.17106","repositories_listed":0,"syntology":null},{"url":null,"slug":"traditional-classification-neural-networks","title":"Traditional Classification Neural Networks are Good Generators: They are Competitive with DDPMs and GANs","date":"2022-11-27","arxiv_id":"2211.14794","repositories_listed":0,"syntology":null},{"url":null,"slug":"cross-domain-microscopy-cell-counting-by","title":"Cross-domain Microscopy Cell Counting by Disentangled Transfer Learning","date":"2022-11-26","arxiv_id":"2211.14638","repositories_listed":0,"syntology":null},{"url":null,"slug":"randomized-conditional-flow-matching-for","title":"Efficient Video Prediction via Sparsely Conditioned Flow Matching","date":"2022-11-26","arxiv_id":"2211.14575","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-detailed-radiance-manifolds-for-high","title":"Learning Detailed Radiance Manifolds for High-Fidelity and 3D-Consistent Portrait Synthesis from Monocular Image","date":"2022-11-25","arxiv_id":"2211.13901","repositories_listed":0,"syntology":null},{"url":null,"slug":"spatext-spatio-textual-representation-for","title":"SpaText: Spatio-Textual Representation for Controllable Image Generation","date":"2022-11-25","arxiv_id":"2211.14305","repositories_listed":0,"syntology":null},{"url":null,"slug":"unifying-conditional-and-unconditional","title":"Unifying conditional and unconditional semantic image synthesis with OCO-GAN","date":"2022-11-25","arxiv_id":"2211.14105","repositories_listed":0,"syntology":null},{"url":null,"slug":"diffusionsdf-conditional-generative-modeling","title":"Diffusion-SDF: Conditional Generative Modeling of Signed Distance Functions","date":"2022-11-24","arxiv_id":"2211.13757","repositories_listed":0,"syntology":null},{"url":null,"slug":"cgof-controllable-3d-face-synthesis-with","title":"CGOF++: Controllable 3D Face Synthesis with Conditional Generative Occupancy Fields","date":"2022-11-23","arxiv_id":"2211.13251","repositories_listed":0,"syntology":null},{"url":"/paper/reco-region-controlled-text-to-image","slug":"reco-region-controlled-text-to-image","title":"ReCo: Region-Controlled Text-to-Image Generation","date":"2022-11-23","arxiv_id":"2211.15518","repositories_listed":0,"syntology":null},{"url":null,"slug":"human-evaluation-of-text-to-image-models-on-a","title":"Human Evaluation of Text-to-Image Models on a Multi-Task Benchmark","date":"2022-11-22","arxiv_id":"2211.12112","repositories_listed":0,"syntology":null},{"url":null,"slug":"rethinking-implicit-neural-representations","title":"Rethinking Implicit Neural Representations for Vision Learners","date":"2022-11-22","arxiv_id":"2211.12040","repositories_listed":0,"syntology":null},{"url":"/paper/retrieval-augmented-multimodal-language","slug":"retrieval-augmented-multimodal-language","title":"Retrieval-Augmented Multimodal Language Modeling","date":"2022-11-22","arxiv_id":"2211.12561","repositories_listed":0,"syntology":null},{"url":null,"slug":"dreamartist-towards-controllable-one-shot","title":"DreamArtist++: Controllable One-Shot Text-to-Image Generation via Positive-Negative Adapter","date":"2022-11-21","arxiv_id":"2211.11337","repositories_listed":0,"syntology":null},{"url":null,"slug":"exploring-the-effectiveness-of-mask-guided","title":"Exploring the Effectiveness of Mask-Guided Feature Modulation as a Mechanism for Localized Style Editing of Real Images","date":"2022-11-21","arxiv_id":"2211.11224","repositories_listed":0,"syntology":null},{"url":null,"slug":"scenecomposer-any-level-semantic-image","title":"SceneComposer: Any-Level Semantic Image Synthesis","date":"2022-11-21","arxiv_id":"2211.11742","repositories_listed":0,"syntology":null},{"url":null,"slug":"timbreclip-connecting-timbre-to-text-and","title":"TimbreCLIP: Connecting Timbre to Text and Images","date":"2022-11-21","arxiv_id":"2211.11225","repositories_listed":0,"syntology":null},{"url":null,"slug":"vectorfusion-text-to-svg-by-abstracting-pixel","title":"VectorFusion: Text-to-SVG by Abstracting Pixel-Based Diffusion Models","date":"2022-11-21","arxiv_id":"2211.11319","repositories_listed":0,"syntology":null},{"url":null,"slug":"ic3d-image-conditioned-3d-diffusion-for-shape","title":"IC3D: Image-Conditioned 3D Diffusion for Shape Generation","date":"2022-11-20","arxiv_id":"2211.10865","repositories_listed":0,"syntology":null},{"url":null,"slug":"single-stage-multi-pose-virtual-try-on","title":"Single Stage Multi-Pose Virtual Try-On","date":"2022-11-19","arxiv_id":"2211.10715","repositories_listed":0,"syntology":null},{"url":null,"slug":"potential-auto-driving-threat-universal-rain","title":"Potential Auto-driving Threat: Universal Rain-removal Attack","date":"2022-11-18","arxiv_id":"2211.09959","repositories_listed":0,"syntology":null},{"url":null,"slug":"umfuse-unified-multi-view-fusion-for-human","title":"UMFuse: Unified Multi View Fusion for Human Editing applications","date":"2022-11-17","arxiv_id":"2211.10157","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-creative-industry-image-generation-dataset","title":"A Creative Industry Image Generation Dataset Based on Captions","date":"2022-11-16","arxiv_id":"2211.09035","repositories_listed":0,"syntology":null},{"url":null,"slug":"arbitrary-style-guidance-for-enhanced","title":"Arbitrary Style Guidance for Enhanced Diffusion-Based Text-to-Image Generation","date":"2022-11-14","arxiv_id":"2211.07751","repositories_listed":0,"syntology":null},{"url":null,"slug":"controllable-gan-synthesis-using-non-rigid","title":"Controllable GAN Synthesis Using Non-Rigid Structure-from-Motion","date":"2022-11-14","arxiv_id":"2211.07195","repositories_listed":0,"syntology":null},{"url":null,"slug":"extreme-generative-image-compression-by","title":"Extreme Generative Image Compression by Learning Text Embedding from Diffusion Models","date":"2022-11-14","arxiv_id":"2211.07793","repositories_listed":0,"syntology":null},{"url":null,"slug":"structural-constrained-virtual-histology","title":"Structural constrained virtual histology staining for human coronary imaging using deep learning","date":"2022-11-12","arxiv_id":"2211.06737","repositories_listed":0,"syntology":null},{"url":null,"slug":"humandiffusion-a-coarse-to-fine-alignment","title":"HumanDiffusion: a Coarse-to-Fine Alignment Diffusion Framework for Controllable Text-Driven Person Image Generation","date":"2022-11-11","arxiv_id":"2211.06235","repositories_listed":0,"syntology":null},{"url":null,"slug":"ssgvs-semantic-scene-graph-to-video-synthesis","title":"SSGVS: Semantic Scene Graph-to-Video Synthesis","date":"2022-11-11","arxiv_id":"2211.06119","repositories_listed":0,"syntology":null},{"url":null,"slug":"self-conditioned-embedding-diffusion-for-text","title":"Self-conditioned Embedding Diffusion for Text Generation","date":"2022-11-08","arxiv_id":"2211.04236","repositories_listed":0,"syntology":null},{"url":null,"slug":"book-cover-synthesis-from-the-summary","title":"Book Cover Synthesis from the Summary","date":"2022-11-03","arxiv_id":"2211.02138","repositories_listed":0,"syntology":null},{"url":null,"slug":"evaluating-a-synthetic-image-dataset","title":"Evaluating a Synthetic Image Dataset Generated with Stable Diffusion","date":"2022-11-03","arxiv_id":"2211.01777","repositories_listed":0,"syntology":null},{"url":null,"slug":"generation-of-anonymous-chest-radiographs","title":"Generation of Anonymous Chest Radiographs Using Latent Diffusion Models for Training Thoracic Abnormality Classification Systems","date":"2022-11-02","arxiv_id":"2211.01323","repositories_listed":0,"syntology":null},{"url":null,"slug":"spot-the-fake-lungs-generating-synthetic","title":"Spot the fake lungs: Generating Synthetic Medical Images using Neural Diffusion Models","date":"2022-11-02","arxiv_id":"2211.00902","repositories_listed":0,"syntology":null},{"url":null,"slug":"textcraft-zero-shot-generation-of-high","title":"CLIP-Sculptor: Zero-Shot Generation of High-Fidelity and Diverse Shapes from Natural Language","date":"2022-11-02","arxiv_id":"2211.01427","repositories_listed":0,"syntology":null},{"url":null,"slug":"gcorf-generative-compositional-radiance","title":"gCoRF: Generative Compositional Radiance Fields","date":"2022-10-31","arxiv_id":"2210.17344","repositories_listed":0,"syntology":null},{"url":null,"slug":"synthetic-id-card-image-generation-for","title":"Synthetic ID Card Image Generation for Improving Presentation Attack Detection","date":"2022-10-31","arxiv_id":"2211.00098","repositories_listed":0,"syntology":null},{"url":null,"slug":"upainting-unified-text-to-image-diffusion","title":"UPainting: Unified Text-to-Image Diffusion Generation with Cross-modal Guidance","date":"2022-10-28","arxiv_id":"2210.16031","repositories_listed":0,"syntology":null},{"url":null,"slug":"accelerating-diffusion-models-via-pre","title":"Accelerating Diffusion Models via Pre-segmentation Diffusion Sampling for Medical Image Segmentation","date":"2022-10-27","arxiv_id":"2210.17408","repositories_listed":0,"syntology":null},{"url":null,"slug":"layer-wise-shared-attention-network-on","title":"A Generic Shared Attention Mechanism for Various Backbone Neural Networks","date":"2022-10-27","arxiv_id":"2210.16101","repositories_listed":0,"syntology":null},{"url":null,"slug":"scoremix-a-scalable-augmentation-strategy-for","title":"ScoreMix: A Scalable Augmentation Strategy for Training GANs with Limited Data","date":"2022-10-27","arxiv_id":"2210.15137","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-practicality-of-sketch-based-visual","title":"Towards Practicality of Sketch-Based Visual Understanding","date":"2022-10-27","arxiv_id":"2210.15146","repositories_listed":0,"syntology":null},{"url":null,"slug":"lafite2-few-shot-text-to-image-generation","title":"Lafite2: Few-shot Text-to-Image Generation","date":"2022-10-25","arxiv_id":"2210.14124","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-latent-structural-causal-models","title":"Learning Latent Structural Causal Models","date":"2022-10-24","arxiv_id":"2210.13583","repositories_listed":0,"syntology":null},{"url":null,"slug":"photo-realistic-neural-domain-randomization","title":"Photo-realistic Neural Domain Randomization","date":"2022-10-23","arxiv_id":"2210.12682","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-visual-tour-of-current-challenges-in","title":"A Visual Tour Of Current Challenges In Multimodal Language Models","date":"2022-10-22","arxiv_id":"2210.12565","repositories_listed":0,"syntology":null},{"url":null,"slug":"context-aware-image-completion","title":"Instance-Aware Image Completion","date":"2022-10-22","arxiv_id":"2210.12350","repositories_listed":0,"syntology":null},{"url":"/paper/diffusion-motion-generate-text-guided-3d","slug":"diffusion-motion-generate-text-guided-3d","title":"Diffusion Motion: Generate Text-Guided 3D Human Motion by Diffusion Model","date":"2022-10-22","arxiv_id":"2210.12315","repositories_listed":0,"syntology":null},{"url":null,"slug":"efficient-hair-style-transfer-with-generative","title":"Efficient Hair Style Transfer with Generative Adversarial Networks","date":"2022-10-22","arxiv_id":"2210.12524","repositories_listed":0,"syntology":null},{"url":"/paper/composing-ensembles-of-pre-trained-models-via","slug":"composing-ensembles-of-pre-trained-models-via","title":"Composing Ensembles of Pre-trained Models via Iterative Consensus","date":"2022-10-20","arxiv_id":"2210.11522","repositories_listed":0,"syntology":null},{"url":null,"slug":"backdoor-attack-and-defense-in-federated","title":"Backdoor Attack and Defense in Federated Generative Adversarial Network-based Medical Image Synthesis","date":"2022-10-19","arxiv_id":"2210.10886","repositories_listed":0,"syntology":null},{"url":null,"slug":"from-play-to-policy-conditional-behavior","title":"From Play to Policy: Conditional Behavior Generation from Uncurated Robot Data","date":"2022-10-18","arxiv_id":"2210.10047","repositories_listed":0,"syntology":null},{"url":null,"slug":"if-gan-a-novel-generator-architecture-with","title":"Improving GANs with a Feature Cycling Generator","date":"2022-10-18","arxiv_id":"2210.09638","repositories_listed":0,"syntology":null},{"url":"/paper/swinv2-imagen-hierarchical-vision-transformer","slug":"swinv2-imagen-hierarchical-vision-transformer","title":"Swinv2-Imagen: Hierarchical Vision Transformer Diffusion Models for Text-to-Image Generation","date":"2022-10-18","arxiv_id":"2210.09549","repositories_listed":0,"syntology":null},{"url":null,"slug":"diffgar-model-agnostic-restoration-from","title":"DiffGAR: Model-Agnostic Restoration from Generative Artifacts Using Image-to-Image Diffusion Models","date":"2022-10-16","arxiv_id":"2210.08573","repositories_listed":0,"syntology":null},{"url":null,"slug":"de-fake-detection-and-attribution-of-fake","title":"DE-FAKE: Detection and Attribution of Fake Images Generated by Text-to-Image Generation Models","date":"2022-10-13","arxiv_id":"2210.06998","repositories_listed":0,"syntology":null},{"url":null,"slug":"fonttransformer-few-shot-high-resolution","title":"FontTransformer: Few-shot High-resolution Chinese Glyph Image Synthesis via Stacked Transformers","date":"2022-10-12","arxiv_id":"2210.06301","repositories_listed":0,"syntology":null},{"url":null,"slug":"controllable-radiance-fields-for-dynamic-face","title":"Controllable Radiance Fields for Dynamic Face Synthesis","date":"2022-10-11","arxiv_id":"2210.05825","repositories_listed":0,"syntology":null},{"url":null,"slug":"style-guided-inference-of-transformer-for","title":"Style-Guided Inference of Transformer for High-resolution Image Synthesis","date":"2022-10-11","arxiv_id":"2210.05533","repositories_listed":0,"syntology":null},{"url":null,"slug":"bridging-clip-and-stylegan-through-latent","title":"Bridging CLIP and StyleGAN through Latent Alignment for Image Editing","date":"2022-10-10","arxiv_id":"2210.04506","repositories_listed":0,"syntology":null},{"url":null,"slug":"f-dm-a-multi-stage-diffusion-model-via","title":"f-DM: A Multi-stage Diffusion Model via Progressive Signal Transformation","date":"2022-10-10","arxiv_id":"2210.04955","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-self-attention-guided-multi-scale-gradient","title":"A Self-attention Guided Multi-scale Gradient GAN for Diversified X-ray Image Synthesis","date":"2022-10-09","arxiv_id":"2210.06334","repositories_listed":0,"syntology":null}],"record_sha256":"fd89aabe9f3a4e828db64a7ca96b6decef9ed93072054518f22b31b858ae7118","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}