mlsanityData to 14 Oct 2026

Illustrator's Depth: Monocular Layer Index Prediction for Image Decomposition

arXiv 2511.17454 ↗First posted 21 Nov 2025cs.CVcited by 1

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Abstract (arXiv)

We introduce Illustrator's Depth, a novel definition of depth that addresses a key challenge in digital content creation: decomposing flat images into editable, ordered layers. Inspired by an artist's compositional process, illustrator's depth infers a layer index to each pixel, forming an interpretable image decomposition through a discrete, globally consistent ordering of elements optimized for editability. We also propose and train a neural network using a curated dataset of layered vector graphics to predict layering directly from raster inputs. Our layer index inference unlocks a range of powerful downstream applications. In particular, it significantly outperforms state-of-the-art baselines for image vectorization while also enabling high-fidelity text-to-vector-graphics generation, automatic 3D relief generation from 2D images, and intuitive depth-aware editing. By reframing depth from a physical quantity to a creative abstraction, illustrator's depth prediction offers a new foundation for editable image decomposition.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 47 of its 69 references that are in the map. First posted on arXiv 21 Nov 2025.

Builds on

47 of 69 references.

References · 47

  1. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,863
  2. 2018The Unreasonable Effectiveness of Deep Features as a Perceptual Metriccited by 11,177
  3. 2023Segment Anythingcited by 8,234
  4. 2023DINOv2: Learning Robust Visual Features without Supervisioncited by 7,974
  5. 2017Mask R-CNNcited by 7,277
  6. 2024SAM 2: Segment Anything in Images and Videoscited by 2,863
  7. 2021CLIPScore: A Reference-free Evaluation Metric for Image Captioningcited by 2,424
  8. 2021Masked-attention Mask Transformer for Universal Image Segmentationcited by 2,351
  9. 2019Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-shot Cross-dataset Transfercited by 1,495
  10. 2014Depth Map Prediction from a Single Image using a Multi-Scale Deep Networkcited by 1,274
  11. 2025FLUX.1 Kontext: Flow Matching for In-Context Image Generation and Editing in Latent Spacecited by 1,006
  12. 2018Panoptic Segmentationcited by 802
35 more
  1. 2018Deep Ordinal Regression Network for Monocular Depth Estimationcited by 723
  2. 2019Panoptic Feature Pyramid Networkscited by 645
  3. 2020AdaBins: Depth Estimation using Adaptive Binscited by 601
  4. 2024Depth Pro: Sharp Monocular Metric Depth in Less Than a Secondcited by 404
  5. 2019Panoptic-DeepLabcited by 363
  6. 2023DreamSim: Learning New Dimensions of Human Visual Similarity using Synthetic Datacited by 337
  7. 2025Video models are zero-shot learners and reasonerscited by 220
  8. 2020Real-Time High-Resolution Background Mattingcited by 173
  9. 2021Im2Vec: Synthesizing Vector Graphics without Vector Supervisioncited by 116
  10. 2024Transparent Image Layer Diffusion using Latent Transparencycited by 114
  11. 2021Deep Occlusion-Aware Instance Segmentation with Overlapping BiLayerscited by 104
  12. 2015Semantic Amodal Segmentationcited by 103
  13. 2023StarVector: Generating Scalable Vector Graphics Code from Images and Textcited by 102
  14. 2019A Learned Representation for Scalable Vector Graphicscited by 91
  15. 2022Towards Layer-wise Image Vectorizationcited by 79
  16. 2025OmniSVG: A Unified Scalable Vector Graphics Generation Modelcited by 74
  17. 2024ObjectDrop: Bootstrapping Counterfactuals for Photorealistic Object Removal and Insertioncited by 71
  18. 2024Empowering LLMs to Understand and Generate Complex Vector Graphicscited by 66
  19. 2020Amodal Segmentation Based on Visible Region Segmentation and Shape Priorcited by 43
  20. 2025LayerTracer: Cognitive-Aligned Layered SVG Synthesis via Diffusion Transformercited by 43
  21. 2025Rendering-Aware Reinforcement Learning for Vector Graphics Generationcited by 39
  22. 2022Amodal Panoptic Segmentationcited by 38
  23. 2024Generative Omnimatte: Learning to Decompose Video into Layerscited by 38
  24. 2025ART: Anonymous Region Transformer for Variable Multi-Layer Transparent Image Generationcited by 37
  25. 2022AISFormer: Amodal Instance Segmentation with Transformercited by 35
  26. 2024Generative Image Layer Decomposition with Visual Effectscited by 34
  27. 2024Text-to-Vector Generation with Neural Path Representationcited by 33
  28. 2021Instance-wise Occlusion and Depth Orders in Natural Scenescited by 31
  29. 2018Peeking Behind Objects: Layered Depth Prediction from a Single Imagecited by 23
  30. 2025NeuralSVG: An Implicit Representation for Text-to-Vector Generationcited by 17
  31. 2015Monocular Object Instance Segmentation and Depth Ordering with CNNscited by 14
  32. 2024Segmentation-guided Layer-wise Image Vectorization with Gradient Fillscited by 11
  33. 2025LayerPeeler: Autoregressive Peeling for Layer-wise Image Vectorizationcited by 8
  34. 2024Image Vectorization with Depth: convexified shape layers with depth orderingcited by 4
  35. 2025Instance Segmentation of Scene Sketches Using Natural Image Priorscited by 4

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 1.

1 paper.

  1. 2026IdEst: Assessing Self-Supervised Learning Representations via Intrinsic Dimensioncited by 2