{"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/43","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":43,"pages_in_order":67,"rows_per_page":100,"rows":[4201,4300],"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/42","next":"/task/image-generation/papers/44","papers":[{"url":null,"slug":"training-free-color-style-disentanglement-for","title":"Training-free Color-Style Disentanglement for Constrained Text-to-Image Synthesis","date":"2024-09-04","arxiv_id":"2409.02429","repositories_listed":0,"syntology":null},{"url":null,"slug":"qid-2-an-image-conditioned-diffusion-model","title":"QID$^2$: An Image-Conditioned Diffusion Model for Q-space Up-sampling of DWI Data","date":"2024-09-03","arxiv_id":"2409.02309","repositories_listed":0,"syntology":null},{"url":null,"slug":"dpdedit-detail-preserved-diffusion-models-for","title":"DPDEdit: Detail-Preserved Diffusion Models for Multimodal Fashion Image Editing","date":"2024-09-02","arxiv_id":"2409.01086","repositories_listed":0,"syntology":null},{"url":null,"slug":"from-bird-s-eye-to-street-view-crafting","title":"From Bird's-Eye to Street View: Crafting Diverse and Condition-Aligned Images with Latent Diffusion Model","date":"2024-09-02","arxiv_id":"2409.01014","repositories_listed":0,"syntology":null},{"url":null,"slug":"spdiffusion-semantic-protection-diffusion-for","title":"SPDiffusion: Semantic Protection Diffusion for Multi-concept Text-to-image Generation","date":"2024-09-02","arxiv_id":"2409.01327","repositories_listed":0,"syntology":null},{"url":null,"slug":"remove-a-reference-free-metric-for-object","title":"ReMOVE: A Reference-free Metric for Object Erasure","date":"2024-09-01","arxiv_id":"2409.00707","repositories_listed":0,"syntology":null},{"url":null,"slug":"accurate-compression-of-text-to-image","title":"Accurate Compression of Text-to-Image Diffusion Models via Vector Quantization","date":"2024-08-31","arxiv_id":"2409.00492","repositories_listed":0,"syntology":null},{"url":null,"slug":"training-free-sketch-guided-diffusion-with","title":"Training-Free Sketch-Guided Diffusion with Latent Optimization","date":"2024-08-31","arxiv_id":"2409.00313","repositories_listed":0,"syntology":null},{"url":null,"slug":"text-to-image-generation-via-energy-based","title":"Text-to-Image Generation Via Energy-Based CLIP","date":"2024-08-30","arxiv_id":"2408.17046","repositories_listed":0,"syntology":null},{"url":null,"slug":"vq4dit-efficient-post-training-vector","title":"VQ4DiT: Efficient Post-Training Vector Quantization for Diffusion Transformers","date":"2024-08-30","arxiv_id":"2408.17131","repositories_listed":0,"syntology":null},{"url":null,"slug":"csgo-content-style-composition-in-text-to","title":"CSGO: Content-Style Composition in Text-to-Image Generation","date":"2024-08-29","arxiv_id":"2408.16766","repositories_listed":0,"syntology":null},{"url":null,"slug":"gameir-a-large-scale-synthesized-ground-truth","title":"GameIR: A Large-Scale Synthesized Ground-Truth Dataset for Image Restoration over Gaming Content","date":"2024-08-29","arxiv_id":"2408.16866","repositories_listed":0,"syntology":null},{"url":"/paper/self-improving-diffusion-models-with","slug":"self-improving-diffusion-models-with","title":"Self-Improving Diffusion Models with Synthetic Data","date":"2024-08-29","arxiv_id":"2408.16333","repositories_listed":0,"syntology":null},{"url":null,"slug":"core-context-regularized-text-embedding","title":"CoRe: Context-Regularized Text Embedding Learning for Text-to-Image Personalization","date":"2024-08-28","arxiv_id":"2408.15914","repositories_listed":0,"syntology":null},{"url":null,"slug":"disentangled-diffusion-autoencoder-for","title":"Disentangled Diffusion Autoencoder for Harmonization of Multi-site Neuroimaging Data","date":"2024-08-28","arxiv_id":"2408.15890","repositories_listed":0,"syntology":null},{"url":null,"slug":"hand1000-generating-realistic-hands-from-text","title":"Hand1000: Generating Realistic Hands from Text with Only 1,000 Images","date":"2024-08-28","arxiv_id":"2408.15461","repositories_listed":0,"syntology":null},{"url":null,"slug":"build-a-scene-interactive-3d-layout-control","title":"Build-A-Scene: Interactive 3D Layout Control for Diffusion-Based Image Generation","date":"2024-08-27","arxiv_id":"2408.14819","repositories_listed":0,"syntology":null},{"url":null,"slug":"crossviewdiff-a-cross-view-diffusion-model","title":"CrossViewDiff: A Cross-View Diffusion Model for Satellite-to-Street View Synthesis","date":"2024-08-27","arxiv_id":"2408.14765","repositories_listed":0,"syntology":null},{"url":null,"slug":"negation-blindness-in-large-language-models","title":"Negation Blindness in Large Language Models: Unveiling the NO Syndrome in Image Generation","date":"2024-08-27","arxiv_id":"2409.00105","repositories_listed":0,"syntology":null},{"url":null,"slug":"reflective-human-machine-co-adaptation-for","title":"Reflective Human-Machine Co-adaptation for Enhanced Text-to-Image Generation Dialogue System","date":"2024-08-27","arxiv_id":"2409.07464","repositories_listed":0,"syntology":null},{"url":null,"slug":"sequential-scanning-dual-energy-ct-imaging","title":"Sequential-Scanning Dual-Energy CT Imaging Using High Temporal Resolution Image Reconstruction and Error-Compensated Material Basis Image Generation","date":"2024-08-27","arxiv_id":"2408.14754","repositories_listed":0,"syntology":null},{"url":null,"slug":"conceptmix-a-compositional-image-generation","title":"ConceptMix: A Compositional Image Generation Benchmark with Controllable Difficulty","date":"2024-08-26","arxiv_id":"2408.14339","repositories_listed":0,"syntology":null},{"url":null,"slug":"foodfusion-a-novel-approach-for-food-image","title":"Foodfusion: A Novel Approach for Food Image Composition via Diffusion Models","date":"2024-08-26","arxiv_id":"2408.14135","repositories_listed":0,"syntology":null},{"url":null,"slug":"prior-learning-in-introspective-vaes","title":"Prior Learning in Introspective VAEs","date":"2024-08-25","arxiv_id":"2408.13805","repositories_listed":0,"syntology":null},{"url":null,"slug":"rt-attack-jailbreaking-text-to-image-models","title":"HTS-Attack: Heuristic Token Search for Jailbreaking Text-to-Image Models","date":"2024-08-25","arxiv_id":"2408.13896","repositories_listed":0,"syntology":null},{"url":null,"slug":"variational-autoencoder-based-neural-network","title":"Variational autoencoder-based neural network model compression","date":"2024-08-25","arxiv_id":"2408.14513","repositories_listed":0,"syntology":null},{"url":null,"slug":"explainable-concept-generation-through-vision","title":"Explainable Concept Generation through Vision-Language Preference Learning","date":"2024-08-24","arxiv_id":"2408.13438","repositories_listed":0,"syntology":null},{"url":null,"slug":"prompt-softbox-prompt-a-free-text-embedding","title":"Prompt-Softbox-Prompt: A free-text Embedding Control for Image Editing","date":"2024-08-24","arxiv_id":"2408.13623","repositories_listed":0,"syntology":null},{"url":null,"slug":"easycontrol-transfer-controlnet-to-video","title":"EasyControl: Transfer ControlNet to Video Diffusion for Controllable Generation and Interpolation","date":"2024-08-23","arxiv_id":"2408.13005","repositories_listed":0,"syntology":null},{"url":null,"slug":"g3fa-geometry-guided-gan-for-face-animation","title":"G3FA: Geometry-guided GAN for Face Animation","date":"2024-08-23","arxiv_id":"2408.13049","repositories_listed":0,"syntology":null},{"url":null,"slug":"shape-preserving-generation-of-food-images","title":"Shape-Preserving Generation of Food Images for Automatic Dietary Assessment","date":"2024-08-23","arxiv_id":"2408.13358","repositories_listed":0,"syntology":null},{"url":null,"slug":"dimerec-a-unified-framework-for-enhanced","title":"DimeRec: A Unified Framework for Enhanced Sequential Recommendation via Generative Diffusion Models","date":"2024-08-22","arxiv_id":"2408.12153","repositories_listed":0,"syntology":null},{"url":null,"slug":"dynamic-product-image-generation-and","title":"Dynamic Product Image Generation and Recommendation at Scale for Personalized E-commerce","date":"2024-08-22","arxiv_id":"2408.12392","repositories_listed":0,"syntology":null},{"url":null,"slug":"meddit-a-knowledge-controlled-diffusion","title":"MedDiT: A Knowledge-Controlled Diffusion Transformer Framework for Dynamic Medical Image Generation in Virtual Simulated Patient","date":"2024-08-22","arxiv_id":"2408.12236","repositories_listed":0,"syntology":null},{"url":null,"slug":"unlocking-intrinsic-fairness-in-stable","title":"Rethinking Training for De-biasing Text-to-Image Generation: Unlocking the Potential of Stable Diffusion","date":"2024-08-22","arxiv_id":"2408.12692","repositories_listed":0,"syntology":null},{"url":null,"slug":"frap-faithful-and-realistic-text-to-image","title":"FRAP: Faithful and Realistic Text-to-Image Generation with Adaptive Prompt Weighting","date":"2024-08-21","arxiv_id":"2408.11706","repositories_listed":0,"syntology":null},{"url":null,"slug":"iterative-object-count-optimization-for-text","title":"Detection-Driven Object Count Optimization for Text-to-Image Diffusion Models","date":"2024-08-21","arxiv_id":"2408.11721","repositories_listed":0,"syntology":null},{"url":null,"slug":"pixel-is-not-a-barrier-an-effective-evasion","title":"Pixel Is Not A Barrier: An Effective Evasion Attack for Pixel-Domain Diffusion Models","date":"2024-08-21","arxiv_id":"2408.11810","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-grey-box-attack-against-latent-diffusion","title":"A Grey-box Attack against Latent Diffusion Model-based Image Editing by Posterior Collapse","date":"2024-08-20","arxiv_id":"2408.10901","repositories_listed":0,"syntology":null},{"url":null,"slug":"ms-3-d-a-rg-flow-based-regularization-for-gan","title":"MS$^3$D: A RG Flow-Based Regularization for GAN Training with Limited Data","date":"2024-08-20","arxiv_id":"2408.11135","repositories_listed":0,"syntology":null},{"url":null,"slug":"diff2ct-diffusion-learning-to-reconstruct","title":"Reconstruct Spine CT from Biplanar X-Rays via Diffusion Learning","date":"2024-08-19","arxiv_id":"2408.09731","repositories_listed":0,"syntology":null},{"url":null,"slug":"saner-annotation-free-societal-attribute","title":"SANER: Annotation-free Societal Attribute Neutralizer for Debiasing CLIP","date":"2024-08-19","arxiv_id":"2408.10202","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-brittleness-of-ai-generated-image","title":"The Brittleness of AI-Generated Image Watermarking Techniques: Examining Their Robustness Against Visual Paraphrasing Attacks","date":"2024-08-19","arxiv_id":"2408.10446","repositories_listed":0,"syntology":null},{"url":null,"slug":"deformation-aware-gan-for-medical-image","title":"Deformation-aware GAN for Medical Image Synthesis with Substantially Misaligned Pairs","date":"2024-08-18","arxiv_id":"2408.09432","repositories_listed":0,"syntology":null},{"url":null,"slug":"comparative-analysis-of-generative-models","title":"Comparative Analysis of Generative Models: Enhancing Image Synthesis with VAEs, GANs, and Stable Diffusion","date":"2024-08-16","arxiv_id":"2408.08751","repositories_listed":0,"syntology":null},{"url":null,"slug":"sketchref-a-benchmark-dataset-and-evaluation","title":"SketchRef: A Benchmark Dataset and Evaluation Metrics for Automated Sketch Synthesis","date":"2024-08-16","arxiv_id":"2408.08623","repositories_listed":0,"syntology":null},{"url":null,"slug":"accelerated-image-aware-generative-diffusion","title":"Accelerated Image-Aware Generative Diffusion Modeling","date":"2024-08-15","arxiv_id":"2408.08306","repositories_listed":0,"syntology":null},{"url":null,"slug":"jpeg-lm-llms-as-image-generators-with","title":"JPEG-LM: LLMs as Image Generators with Canonical Codec Representations","date":"2024-08-15","arxiv_id":"2408.08459","repositories_listed":0,"syntology":null},{"url":null,"slug":"boosting-unconstrained-face-recognition-with","title":"Boosting Unconstrained Face Recognition with Targeted Style Adversary","date":"2024-08-14","arxiv_id":"2408.07642","repositories_listed":0,"syntology":null},{"url":null,"slug":"magicface-training-free-universal-style-human","title":"MagicFace: Training-free Universal-Style Human Image Customized Synthesis","date":"2024-08-14","arxiv_id":"2408.07433","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-comprehensive-survey-on-synthetic-infrared","title":"A Comprehensive Survey on Synthetic Infrared Image synthesis","date":"2024-08-13","arxiv_id":"2408.06868","repositories_listed":0,"syntology":null},{"url":null,"slug":"difflora-generating-personalized-low-rank","title":"DiffLoRA: Generating Personalized Low-Rank Adaptation Weights with Diffusion","date":"2024-08-13","arxiv_id":"2408.06740","repositories_listed":0,"syntology":null},{"url":null,"slug":"hybrid-sd-edge-cloud-collaborative-inference","title":"Hybrid SD: Edge-Cloud Collaborative Inference for Stable Diffusion Models","date":"2024-08-13","arxiv_id":"2408.06646","repositories_listed":0,"syntology":null},{"url":null,"slug":"selora-self-expanding-low-rank-adaptation-of","title":"SeLoRA: Self-Expanding Low-Rank Adaptation of Latent Diffusion Model for Medical Image Synthesis","date":"2024-08-13","arxiv_id":"2408.07196","repositories_listed":0,"syntology":null},{"url":null,"slug":"novel-view-synthesis-from-a-single-image-with","title":"3D-free meets 3D priors: Novel View Synthesis from a Single Image with Pretrained Diffusion Guidance","date":"2024-08-12","arxiv_id":"2408.06157","repositories_listed":0,"syntology":null},{"url":null,"slug":"prompt-recovery-for-image-generation-models-a","title":"Prompt Recovery for Image Generation Models: A Comparative Study of Discrete Optimizers","date":"2024-08-12","arxiv_id":"2408.06502","repositories_listed":0,"syntology":null},{"url":null,"slug":"artworks-reimagined-exploring-human-ai-co","title":"Artworks Reimagined: Exploring Human-AI Co-Creation through Body Prompting","date":"2024-08-10","arxiv_id":"2408.05476","repositories_listed":0,"syntology":null},{"url":null,"slug":"daft-gan-dual-affine-transformation","title":"DAFT-GAN: Dual Affine Transformation Generative Adversarial Network for Text-Guided Image Inpainting","date":"2024-08-09","arxiv_id":"2408.04962","repositories_listed":0,"syntology":null},{"url":null,"slug":"instruction-tuning-free-visual-token","title":"Instruction Tuning-free Visual Token Complement for Multimodal LLMs","date":"2024-08-09","arxiv_id":"2408.05019","repositories_listed":0,"syntology":null},{"url":null,"slug":"zero-shot-uncertainty-quantification-using","title":"Zero-Shot Uncertainty Quantification using Diffusion Probabilistic Models","date":"2024-08-08","arxiv_id":"2408.04718","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-comparative-study-of-generative-adversarial","title":"A comparative study of generative adversarial networks for image recognition algorithms based on deep learning and traditional methods","date":"2024-08-07","arxiv_id":"2408.03568","repositories_listed":0,"syntology":null},{"url":null,"slug":"counterfactuals-and-uncertainty-based","title":"Counterfactuals and Uncertainty-Based Explainable Paradigm for the Automated Detection and Segmentation of Renal Cysts in Computed Tomography Images: A Multi-Center Study","date":"2024-08-07","arxiv_id":"2408.03789","repositories_listed":0,"syntology":null},{"url":null,"slug":"2408-03001","title":"One Framework to Rule Them All: Unifying Multimodal Tasks with LLM Neural-Tuning","date":"2024-08-06","arxiv_id":"2408.03001","repositories_listed":0,"syntology":null},{"url":null,"slug":"2408-03178","title":"An Object is Worth 64x64 Pixels: Generating 3D Object via Image Diffusion","date":"2024-08-06","arxiv_id":"2408.03178","repositories_listed":0,"syntology":null},{"url":null,"slug":"2408-03209","title":"IPAdapter-Instruct: Resolving Ambiguity in Image-based Conditioning using Instruct Prompts","date":"2024-08-06","arxiv_id":"2408.03209","repositories_listed":0,"syntology":null},{"url":null,"slug":"attacks-and-defenses-for-generative-diffusion","title":"Attacks and Defenses for Generative Diffusion Models: A Comprehensive Survey","date":"2024-08-06","arxiv_id":"2408.03400","repositories_listed":0,"syntology":null},{"url":null,"slug":"2408-02054","title":"Step Saver: Predicting Minimum Denoising Steps for Diffusion Model Image Generation","date":"2024-08-04","arxiv_id":"2408.02054","repositories_listed":0,"syntology":null},{"url":null,"slug":"2408-02078","title":"LDFaceNet: Latent Diffusion-based Network for High-Fidelity Deepfake Generation","date":"2024-08-04","arxiv_id":"2408.02078","repositories_listed":0,"syntology":null},{"url":null,"slug":"2408-02157","title":"PanoFree: Tuning-Free Holistic Multi-view Image Generation with Cross-view Self-Guidance","date":"2024-08-04","arxiv_id":"2408.02157","repositories_listed":0,"syntology":null},{"url":null,"slug":"2408-01723","title":"A Novel Evaluation Framework for Image2Text Generation","date":"2024-08-03","arxiv_id":"2408.01723","repositories_listed":0,"syntology":null},{"url":null,"slug":"2408-01812","title":"SkyDiffusion: Ground-to-Aerial Image Synthesis with Diffusion Models and BEV Paradigm","date":"2024-08-03","arxiv_id":"2408.01812","repositories_listed":0,"syntology":null},{"url":null,"slug":"2408-01014","title":"EIUP: A Training-Free Approach to Erase Non-Compliant Concepts Conditioned on Implicit Unsafe Prompts","date":"2024-08-02","arxiv_id":"2408.01014","repositories_listed":0,"syntology":null},{"url":null,"slug":"2408-00707","title":"Synthetic dual image generation for reduction of labeling efforts in semantic segmentation of micrographs with a customized metric function","date":"2024-08-01","arxiv_id":"2408.00707","repositories_listed":0,"syntology":null},{"url":null,"slug":"2408-00891","title":"Temporal Evolution of Knee Osteoarthritis: A Diffusion-based Morphing Model for X-ray Medical Image Synthesis","date":"2024-08-01","arxiv_id":"2408.00891","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-new-approach-for-encoding-code-and","title":"A new approach for encoding code and assisting code understanding","date":"2024-08-01","arxiv_id":"2408.00521","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-simple-background-augmentation-method-for","title":"A Simple Background Augmentation Method for Object Detection with Diffusion Model","date":"2024-08-01","arxiv_id":"2408.00350","repositories_listed":0,"syntology":null},{"url":null,"slug":"2407-21428","title":"Deformable 3D Shape Diffusion Model","date":"2024-07-31","arxiv_id":"2407.21428","repositories_listed":0,"syntology":null},{"url":null,"slug":"fine-gained-zero-shot-video-sampling","title":"Fine-gained Zero-shot Video Sampling","date":"2024-07-31","arxiv_id":"2407.21475","repositories_listed":0,"syntology":null},{"url":null,"slug":"vulnerabilities-in-ai-generated-image","title":"Vulnerabilities in AI-generated Image Detection: The Challenge of Adversarial Attacks","date":"2024-07-30","arxiv_id":"2407.20836","repositories_listed":0,"syntology":null},{"url":null,"slug":"maskinversion-localized-embeddings-via","title":"MaskInversion: Localized Embeddings via Optimization of Explainability Maps","date":"2024-07-29","arxiv_id":"2407.20034","repositories_listed":0,"syntology":null},{"url":null,"slug":"retinex-diffusion-on-controlling-illumination","title":"Retinex-Diffusion: On Controlling Illumination Conditions in Diffusion Models via Retinex Theory","date":"2024-07-29","arxiv_id":"2407.20785","repositories_listed":0,"syntology":null},{"url":null,"slug":"artificial-immunofluorescence-in-a-flash","title":"Artificial Immunofluorescence in a Flash: Rapid Synthetic Imaging from Brightfield Through Residual Diffusion","date":"2024-07-25","arxiv_id":"2407.17882","repositories_listed":0,"syntology":null},{"url":null,"slug":"guided-latent-slot-diffusion-for-object","title":"Guided Latent Slot Diffusion for Object-Centric Learning","date":"2024-07-25","arxiv_id":"2407.17929","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-adaptive-gradient-regularization-method","title":"Adaptive Gradient Regularization: A Faster and Generalizable Optimization Technique for Deep Neural Networks","date":"2024-07-24","arxiv_id":"2407.16944","repositories_listed":0,"syntology":null},{"url":null,"slug":"lpgen-enhancing-high-fidelity-landscape","title":"Artistic Intelligence: A Diffusion-Based Framework for High-Fidelity Landscape Painting Synthesis","date":"2024-07-24","arxiv_id":"2407.17229","repositories_listed":0,"syntology":null},{"url":null,"slug":"utilizing-generative-adversarial-networks-for-1","title":"Utilizing Generative Adversarial Networks for Image Data Augmentation and Classification of Semiconductor Wafer Dicing Induced Defects","date":"2024-07-24","arxiv_id":"2407.20268","repositories_listed":0,"syntology":null},{"url":null,"slug":"viper-visual-personalization-of-generative","title":"ViPer: Visual Personalization of Generative Models via Individual Preference Learning","date":"2024-07-24","arxiv_id":"2407.17365","repositories_listed":0,"syntology":null},{"url":null,"slug":"distilling-vision-language-foundation-models","title":"Distilling Vision-Language Foundation Models: A Data-Free Approach via Prompt Diversification","date":"2024-07-21","arxiv_id":"2407.15155","repositories_listed":0,"syntology":null},{"url":null,"slug":"lsregen-large-scale-regional-generator-via","title":"LSReGen: Large-Scale Regional Generator via Backward Guidance Framework","date":"2024-07-21","arxiv_id":"2407.15066","repositories_listed":0,"syntology":null},{"url":null,"slug":"mededit-counterfactual-diffusion-based-image","title":"MedEdit: Counterfactual Diffusion-based Image Editing on Brain MRI","date":"2024-07-21","arxiv_id":"2407.15270","repositories_listed":0,"syntology":null},{"url":null,"slug":"variational-potential-flow-a-novel","title":"Variational Potential Flow: A Novel Probabilistic Framework for Energy-Based Generative Modelling","date":"2024-07-21","arxiv_id":"2407.15238","repositories_listed":0,"syntology":null},{"url":null,"slug":"diffusion-models-as-data-mining-tools","title":"Diffusion Models as Data Mining Tools","date":"2024-07-20","arxiv_id":"2408.02752","repositories_listed":0,"syntology":null},{"url":null,"slug":"infty-brush-controllable-large-image","title":"$\\infty$-Brush: Controllable Large Image Synthesis with Diffusion Models in Infinite Dimensions","date":"2024-07-20","arxiv_id":"2407.14709","repositories_listed":0,"syntology":null},{"url":null,"slug":"latent-pollution-model-the-hidden-carbon","title":"Latent Pollution Model: The Hidden Carbon Footprint in 3D Image Synthesis","date":"2024-07-20","arxiv_id":"2407.14892","repositories_listed":0,"syntology":null},{"url":null,"slug":"are-handcrafted-filters-helpful-for","title":"Are handcrafted filters helpful for attributing AI-generated images?","date":"2024-07-19","arxiv_id":"2407.14570","repositories_listed":0,"syntology":null},{"url":null,"slug":"controllable-and-efficient-multi-class","title":"Controllable and Efficient Multi-Class Pathology Nuclei Data Augmentation using Text-Conditioned Diffusion Models","date":"2024-07-19","arxiv_id":"2407.14426","repositories_listed":0,"syntology":null},{"url":null,"slug":"panoptic-segmentation-of-mammograms-with-text","title":"Panoptic Segmentation of Mammograms with Text-To-Image Diffusion Model","date":"2024-07-19","arxiv_id":"2407.14326","repositories_listed":0,"syntology":null},{"url":null,"slug":"time-series-generative-learning-with","title":"Time Series Generative Learning with Application to Brain Imaging Analysis","date":"2024-07-19","arxiv_id":"2407.14003","repositories_listed":0,"syntology":null},{"url":null,"slug":"image-inpainting-models-are-effective-tools","title":"Image Inpainting Models are Effective Tools for Instruction-guided Image Editing","date":"2024-07-18","arxiv_id":"2407.13139","repositories_listed":0,"syntology":null},{"url":null,"slug":"safe-sd-safe-and-traceable-stable-diffusion","title":"Safe-SD: Safe and Traceable Stable Diffusion with Text Prompt Trigger for Invisible Generative Watermarking","date":"2024-07-18","arxiv_id":"2407.13188","repositories_listed":0,"syntology":null}],"record_sha256":"09bff661ea75d7741806891234cdab57ff02c3a9c370f6a8a4663b6fe872ae59","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}