mlsanityData to 14 Oct 2026

MIGC++: Advanced Multi-Instance Generation Controller for Image Synthesis

arXiv 2407.02329 ↗First posted 2 Jul 2024cs.CVcited by 35

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Abstract (arXiv)

We introduce the Multi-Instance Generation (MIG) task, which focuses on generating multiple instances within a single image, each accurately placed at predefined positions with attributes such as category, color, and shape, strictly following user specifications. MIG faces three main challenges: avoiding attribute leakage between instances, supporting diverse instance descriptions, and maintaining consistency in iterative generation. To address attribute leakage, we propose the Multi-Instance Generation Controller (MIGC). MIGC generates multiple instances through a divide-and-conquer strategy, breaking down multi-instance shading into single-instance tasks with singular attributes, later integrated. To provide more types of instance descriptions, we developed MIGC++. MIGC++ allows attribute control through text & images and position control through boxes & masks. Lastly, we introduced the Consistent-MIG algorithm to enhance the iterative MIG ability of MIGC and MIGC++. This algorithm ensures consistency in unmodified regions during the addition, deletion, or modification of instances, and preserves the identity of instances when their attributes are changed. We introduce the COCO-MIG and Multimodal-MIG benchmarks to evaluate these methods. Extensive experiments on these benchmarks, along with the COCO-Position benchmark and DrawBench, demonstrate that our methods substantially outperform existing techniques, maintaining precise control over aspects including position, attribute, and quantity. Project page: https://github.com/limuloo/MIGC.

Key facts. Cited by 35 papers in the map (data through 14 Oct 2026). Builds on 77 of its 82 references that are in the map. First posted on arXiv 2 Jul 2024.

Builds on

77 of 82 references.

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38 more
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Citing papers per year: 2024: 9; 2025: 16; 2026: 10.

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  1. 2025In-Context Edit: Enabling Instructional Image Editing with In-Context Generation in Large Scale Diffusion Transformercited by 204
  2. 2024Robust Watermarking Using Generative Priors Against Image Editing: From Benchmarking to Advancescited by 110
  3. 2025Set You Straight: Auto-Steering Denoising Trajectories to Sidestep Unwanted Conceptscited by 62
  4. 20243DIS: Depth-Driven Decoupled Instance Synthesis for Text-to-Image Generationcited by 37
  5. 2025Does FLUX Already Know How to Perform Physically Plausible Image Composition?cited by 32
  6. 2025DragFlow: Unleashing DiT Priors with Region Based Supervision for Drag Editingcited by 29
  7. 2025DreamRenderer: Taming Multi-Instance Attribute Control in Large-Scale Text-to-Image Modelscited by 28
  8. 2025From Zero to Detail: Deconstructing Ultra-High-Definition Image Restoration from Progressive Spectral Perspectivecited by 23
  9. 2024IFAdapter: Instance Feature Control for Grounded Text-to-Image Generationcited by 18
  10. 2024Imagine and Seek: Improving Composed Image Retrieval with an Imagined Proxycited by 18
  11. 2025ContextGen: Contextual Layout Anchoring for Identity-Consistent Multi-Instance Generationcited by 18
  12. 2025UltraHR-100K: Enhancing UHR Image Synthesis with A Large-Scale High-Quality Datasetcited by 18
23 more
  1. 2025DreamLayer: Simultaneous Multi-Layer Generation via Diffusion Modecited by 17
  2. 2026LUVE : Latent-Cascaded Ultra-High-Resolution Video Generation with Dual Frequency Expertscited by 15
  3. 2024LAION-SG: An Enhanced Large-Scale Dataset for Training Complex Image-Text Models with Structural Annotationscited by 12
  4. 2024Enhancing MMDiT-Based Text-to-Image Models for Similar Subject Generationcited by 11
  5. 2025InstanceAssemble: Layout-Aware Image Generation via Instance Assembling Attentioncited by 10
  6. 2025BideDPO: Conditional Image Generation with Simultaneous Text and Condition Alignmentcited by 10
  7. 2024O-Mamba: O-shape State-Space Model for Underwater Image Enhancementcited by 9
  8. 2024CC-Diff: Enhancing Contextual Coherence in Remote Sensing Image Synthesiscited by 8
  9. 2026WeEdit: A Dataset, Benchmark and Glyph-Guided Framework for Text-centric Image Editingcited by 7
  10. 2026From Zero to Detail: A Progressive Spectral Decoupling Paradigm for UHD Image Restoration with New Benchmarkcited by 7
  11. 2025Inversion-DPO: Precise and Efficient Post-Training for Diffusion Modelscited by 6
  12. 2025ConsistCompose: Unified Multimodal Layout Control for Image Compositioncited by 5
  13. 2024AnySynth: Harnessing the Power of Image Synthetic Data Generation for Generalized Vision-Language Taskscited by 4
  14. 2025MUSE: Multi-Subject Unified Synthesis via Explicit Layout Semantic Expansioncited by 4
  15. 2025DreamOmni3: Scribble-based Editing and Generationcited by 2
  16. 2026FoleyDirector: Fine-Grained Temporal Steering for Video-to-Audio Generation via Structured Scriptscited by 2
  17. 2026TRACE: High-Fidelity 3D Scene Editing via Tangible Reconstruction and Geometry-Aligned Contextual Video Maskingcited by 2
  18. 2026Envisioning Beyond the Few: Disentangled Semantics and Primitives for Few-Shot Atypical Layout-to-Image Generationcited by 2
  19. 2026PhyEdit: Towards Real-World Object Manipulation via Physically-Grounded Image Editingcited by 1
  20. 2025ROVI: A VLM-LLM Re-Captioned Dataset for Open-Vocabulary Instance-Grounded Text-to-Image Generationcited by 0
  21. 2026OneHOI: Unifying Human-Object Interaction Generation and Editingcited by 0
  22. 2026High-Resolution Artwork Outpainting with Global Blueprint Guidance and Layout Controlcited by 0
  23. 2026ControlRef: Efficient Layout-Guided Multi-Instance Generation via Anchored 4D-RoPEcited by 0