Papers Conditional Text-to-Image Synthesis
“Conditional Text-to-Image Synthesis” 태그가 달린 논문 10편 · 필터 해제
CheXGenBench: A Unified Benchmark For Fidelity, Privacy and Utility of Synthetic Chest Radiographs
We introduce CheXGenBench, a rigorous and multifaceted evaluation framework for synthetic chest radiograph generation that simultaneously assesses fidelity, privacy risks, and clinical utility across state-of-the-art tex…
Conditional Text-to-Image SynthesisTest-time Conditional Text-to-Image Synthesis Using Diffusion Models
We consider the problem of conditional text-to-image synthesis with diffusion models. Most recent works need to either finetune specific parts of the base diffusion model or introduce new trainable parameters, leading to…
Conditional Text-to-Image SynthesisDenoisingImage GenerationZero-Painter: Training-Free Layout Control for Text-to-Image Synthesis
We present Zero-Painter, a novel training-free framework for layout-conditional text-to-image synthesis that facilitates the creation of detailed and controlled imagery from textual prompts. Our method utilizes object ma…
Conditional Text-to-Image SynthesisImage GenerationMIGC: Multi-Instance Generation Controller for Text-to-Image Synthesis
We present a Multi-Instance Generation (MIG) task, simultaneously generating multiple instances with diverse controls in one image. Given a set of predefined coordinates and their corresponding descriptions, the task is …
AttributeConditional Text-to-Image SynthesisImage GenerationInstanceDiffusion: Instance-level Control for Image Generation
Text-to-image diffusion models produce high quality images but do not offer control over individual instances in the image. We introduce InstanceDiffusion that adds precise instance-level control to text-to-image diffusi…
Conditional Text-to-Image SynthesisImage GenerationInstance SegmentationSemantic SegmentationBoxDiff: Text-to-Image Synthesis with Training-Free Box-Constrained Diffusion
Recent text-to-image diffusion models have demonstrated an astonishing capacity to generate high-quality images. However, researchers mainly studied the way of synthesizing images with only text prompts. While some works…
Conditional Text-to-Image SynthesisDenoisingImage GenerationText-to-Image GenerationPrompt-Free Diffusion: Taking "Text" out of Text-to-Image Diffusion Models
Text-to-image (T2I) research has grown explosively in the past year, owing to the large-scale pre-trained diffusion models and many emerging personalization and editing approaches. Yet, one pain point persists: the text …
Conditional Text-to-Image SynthesisImage GenerationImage-VariationPrompt Engineering+1LaCon: Late-Constraint Diffusion for Steerable Guided Image Synthesis
Diffusion models have demonstrated impressive abilities in generating photo-realistic and creative images. To offer more controllability for the generation process, existing studies, termed as early-constraint methods in…
Conditional Image GenerationConditional Text-to-Image SynthesisImage GenerationText-to-Image GenerationGLIGEN: Open-Set Grounded Text-to-Image Generation
Large-scale text-to-image diffusion models have made amazing advances. However, the status quo is to use text input alone, which can impede controllability. In this work, we propose GLIGEN, Grounded-Language-to-Image Gen…
Conditional Text-to-Image SynthesisImage GenerationImage InpaintingLayout-to-Image Generation+2ReCo: Region-Controlled Text-to-Image Generation
Recently, large-scale text-to-image (T2I) models have shown impressive performance in generating high-fidelity images, but with limited controllability, e.g., precisely specifying the content in a specific region with a …
Conditional Text-to-Image SynthesisImage GenerationLayout-to-Image GenerationPosition+2