mlsanityData to 7 Oct 2026

Build-A-Scene: Interactive 3D Layout Control for Diffusion-Based Image Generation

arXiv 2408.14819 ↗First posted 27 Aug 2024cs.CVcited by 18

On the map: Diffusion models → Image generation, text-to-image and editing

Abstract (arXiv)

We propose a diffusion-based approach for Text-to-Image (T2I) generation with interactive 3D layout control. Layout control has been widely studied to alleviate the shortcomings of T2I diffusion models in understanding objects' placement and relationships from text descriptions. Nevertheless, existing approaches for layout control are limited to 2D layouts, require the user to provide a static layout beforehand, and fail to preserve generated images under layout changes. This makes these approaches unsuitable for applications that require 3D object-wise control and iterative refinements, e.g., interior design and complex scene generation. To this end, we leverage the recent advancements in depth-conditioned T2I models and propose a novel approach for interactive 3D layout control. We replace the traditional 2D boxes used in layout control with 3D boxes. Furthermore, we revamp the T2I task as a multi-stage generation process, where at each stage, the user can insert, change, and move an object in 3D while preserving objects from earlier stages. We achieve this through our proposed Dynamic Self-Attention (DSA) module and the consistent 3D object translation strategy. Experiments show that our approach can generate complicated scenes based on 3D layouts, boosting the object generation success rate over the standard depth-conditioned T2I methods by 2x. Moreover, it outperforms other methods in comparison in preserving objects under layout changes. Project Page: urlhttps://abdo-eldesokey.github.io/build-a-scene/

Key facts. Cited by 18 papers in the map (data through 7 Oct 2026). Placed in Image generation, text-to-image and editing, one of 14 directions in Diffusion models. Builds on 44 of its 46 references that are in the map. First posted on arXiv 27 Aug 2024.

Builds on

44 of 46 references.

Closest ancestors · 20

Same direction, newest first

  1. 2024Training-free Composite Scene Generation for Layout-to-Image Synthesis18 Jul
  2. 2024InstantID: Zero-shot Identity-Preserving Generation in Seconds15 Jan
  3. 2023LooseControl: Lifting ControlNet for Generalized Depth Conditioning5 Dec
  4. 2023HiFi Tuner: High-Fidelity Subject-Driven Fine-Tuning for Diffusion Models30 Nov
  5. 2023CustomNet: Zero-shot Object Customization with Variable-Viewpoints in Text-to-Image Diffusion Models30 Oct
  6. 2023LLM Blueprint: Enabling Text-to-Image Generation with Complex and Detailed Prompts16 Oct
  7. 2023IP-Adapter: Text Compatible Image Prompt Adapter for Text-to-Image Diffusion Models13 Aug
  8. 2023Subject-Diffusion:Open Domain Personalized Text-to-Image Generation without Test-time Fine-tuning21 Jul
  9. 2023BoxDiff: Text-to-Image Synthesis with Training-Free Box-Constrained Diffusion20 Jul
  10. 2023Zero-shot spatial layout conditioning for text-to-image diffusion models23 Jun
  11. 2023LLM-grounded Diffusion: Enhancing Prompt Understanding of Text-to-Image Diffusion Models with Large Language Models23 May
  12. 2023LayoutDiffusion: Controllable Diffusion Model for Layout-to-image Generation30 Mar
8 more
  1. 2023T2I-Adapter: Learning Adapters to Dig out More Controllable Ability for Text-to-Image Diffusion Models16 Feb
  2. 2023Adding Conditional Control to Text-to-Image Diffusion Models10 Feb
  3. 2023GLIGEN: Open-Set Grounded Text-to-Image Generation17 Jan
  4. 2022SpaText: Spatio-Textual Representation for Controllable Image Generation25 Nov
  5. 2022DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation25 Aug
  6. 2022Blended Latent Diffusion6 Jun
  7. 2022Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding23 May
  8. 2022Hierarchical Text-Conditional Image Generation with CLIP Latents13 Apr

Other references · 24

  1. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
  2. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  3. 2014Microsoft COCO: Common Objects in Contextcited by 17,498
  4. 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,084
  5. 2020Denoising Diffusion Implicit Modelscited by 9,655
  6. 2023Segment Anythingcited by 8,158
  7. 2023SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesiscited by 4,290
  8. 2022Prompt-to-Prompt Image Editing with Cross Attention Controlcited by 2,409
  9. 2017Arbitrary Style Transfer in Real-time with Adaptive Instance Normalizationcited by 1,998
  10. 2024Depth Anything: Unleashing the Power of Large-Scale Unlabeled Datacited by 1,346
  11. 2022Plug-and-Play Diffusion Features for Text-Driven Image-to-Image Translationcited by 897
  12. 2023MasaCtrl: Tuning-Free Mutual Self-Attention Control for Consistent Image Synthesis and Editingcited by 722
12 more
  1. 2023Text2Video-Zero: Text-to-Image Diffusion Models are Zero-Shot Video Generatorscited by 666
  2. 2023FateZero: Fusing Attentions for Zero-shot Text-based Video Editingcited by 462
  3. 2023LayoutGPT: Compositional Visual Planning and Generation with Large Language Modelscited by 337
  4. 2023Training-Free Layout Control with Cross-Attention Guidancecited by 312
  5. 2023Rerender A Video: Zero-Shot Text-Guided Video-to-Video Translationcited by 253
  6. 2022ReCo: Region-Controlled Text-to-Image Generationcited by 177
  7. 2022Omni3D: A Large Benchmark and Model for 3D Object Detection in the Wildcited by 159
  8. 2024MIGC: Multi-Instance Generation Controller for Text-to-Image Synthesiscited by 123
  9. 2023Real-Time Flying Object Detection with YOLOv8cited by 93
  10. 2022SceneComposer: Any-Level Semantic Image Synthesiscited by 43
  11. 2024Compositional Text-to-Image Generation with Dense Blob Representationscited by 38
  12. 2023LatentMan: Generating Consistent Animated Characters using Image Diffusion Modelscited by 4

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 3; 2025: 8; 2026: 7.

18 papers.

Sort:

By area:

  1. 2024SINGAPO: Single Image Controlled Generation of Articulated Parts in Objectscited by 66
  2. 2025ORIGEN: Zero-Shot 3D Orientation Grounding in Text-to-Image Generationcited by 10
  3. 2025CoT-lized Diffusion: Let's Reinforce T2I Generation Step-by-stepcited by 8
  4. 2025LACONIC: A 3D Layout Adapter for Controllable Image Creationcited by 6
  5. 2025Improving Editability in Image Generation with Layer-wise Memorycited by 5
  6. 2026Untwisting RoPE: Frequency Control for Shared Attention in DiTscited by 4
  7. 2026SeeThrough3D: Occlusion Aware 3D Control in Text-to-Image Generationcited by 4
  8. 2024COMOGen: A Controllable Text-to-3D Multi-object Generation Frameworkcited by 2
  9. 2024SSEditor: Controllable Mask-to-Scene Generation with Diffusion Modelcited by 2
  10. 2025Generative Blocks World: Moving Things Around in Picturescited by 2
  11. 2025Controllable 3D Placement of Objects with Scene-Aware Diffusion Modelscited by 2
  12. 2026Talk2Move: Reinforcement Learning for Text-Instructed Object-Level Geometric Transformation in Scenescited by 2
6 more
  1. 2026POCI-Diff: 3D-Layout Guided Diffusion for Controllable Synthetic Surveillance Data Generationcited by 2
  2. 2025Griffin: Generative Reference and Layout Guided Image Compositioncited by 1
  3. 2025Attacks on Approximate Caches in Text-to-Image Diffusion Modelscited by 0
  4. 2026Thinking in Boxes: 3D Editing in Real Images Made Easycited by 0
  5. 2026BoxCtrl: 3D-Aware Visual Prompting for Geometric Image Editingcited by 0
  6. 2026PoseAdapter: Dual-Stream 2.5D Controllable Image Generation for Complex Multi-Object Scenescited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025Layout2Scene: 3D Semantic Layout Guided Scene Generation via Geometry and Appearance Diffusion Priors
  2. 2025A Two-Stage System for Layout-Controlled Image Generation using Large Language Models and Diffusion Models
  3. 2026Co-generation of Layout and Shape from Text via Autoregressive 3D Diffusion
  4. 2023SSMG: Spatial-Semantic Map Guided Diffusion Model for Free-form Layout-to-Image Generation
  5. 2024Layout Control and Semantic Guidance with Attention Loss Backward for T2I Diffusion Model
  6. 2023R&B: Region and Boundary Aware Zero-shot Grounded Text-to-image Generation
  7. 2024Generating Compositional Scenes via Text-to-image RGBA Instance Generation
  8. 2023Control3D: Towards Controllable Text-to-3D Generation