DiffDecompose: Layer-Wise Decomposition of Alpha-Composited Images via Diffusion Transformers
Zitong Wang, Hang Zhao, Qianyu Zhou, Xuequan Lu, Xiangtai Li, Yiren Song

TL;DR
This paper introduces DiffDecompose, a diffusion Transformer framework for layer-wise decomposition of alpha-composited images, supported by a new large-scale dataset AlphaBlend, enabling better handling of semi-transparent occlusions.
Contribution
The paper presents a novel diffusion Transformer-based approach and a large-scale dataset for transparent and semi-transparent layer decomposition from single images.
Findings
DiffDecompose outperforms existing methods on AlphaBlend and LOGO datasets.
The AlphaBlend dataset supports six real-world decomposition subtasks.
DiffDecompose enables in-context layer prediction without per-layer supervision.
Abstract
Diffusion models have recently motivated great success in many generation tasks like object removal. Nevertheless, existing image decomposition methods struggle to disentangle semi-transparent or transparent layer occlusions due to mask prior dependencies, static object assumptions, and the lack of datasets. In this paper, we delve into a novel task: Layer-Wise Decomposition of Alpha-Composited Images, aiming to recover constituent layers from single overlapped images under the condition of semi-transparent/transparent alpha layer non-linear occlusion. To address challenges in layer ambiguity, generalization, and data scarcity, we first introduce AlphaBlend, the first large-scale and high-quality dataset for transparent and semi-transparent layer decomposition, supporting six real-world subtasks (e.g., translucent flare removal, semi-transparent cell decomposition, glassware…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsIntegrated Circuits and Semiconductor Failure Analysis · Image Processing Techniques and Applications · Industrial Vision Systems and Defect Detection
MethodsDiffusion
