title: Tree-Structured Shading Decomposition
summary: We study inferring a tree-structured representation from a single image for
  object shading. Prior work typically uses the parametric or measured
  representation to model shading, which is neither interpretable nor easily
  editable. We propose using the shade tree representation, which combines basic
  shading nodes and compositing methods to factorize object surface shading. The
  shade tree representation enables novice users who are unfamiliar with the
  physical shading process to edit object shading in an efficient and intuitive
  manner. A main challenge in inferring the shade tree is that the inference
  problem involves both the discrete tree structure and the continuous parameters
  of the tree nodes. We propose a hybrid approach to address this issue. We
  introduce an auto-regressive inference model to generate a rough estimation of
  the tree structure and node parameters, and then we fine-tune the inferred
  shade tree through an optimization algorithm. We show experiments on synthetic
  images, captured reflectance, real images, and non-realistic vector drawings,
  allowing downstream applications such as material editing, vectorized shading,
  and relighting. Project website: https://chen-geng.com/inv-shade-trees
paper_authors._id: 6502a153e9230a325e02309c
paper_authors.name: Chen Geng
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2023-09-15T07:40:22.344Z
paper_authors._id: 6305b64699870e13d3e1cb50
paper_authors.avatarUrl: /avatars/e38fc1ad7b147036b98cd5ac6cd37516.svg
paper_authors.fullname: Chen Geng
paper_authors.type: user
paper_authors.user: MrMorning
paper_authors._id: 6502a153e9230a325e02309d
paper_authors.name: Hong-Xing Yu
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2023-09-15T07:40:19.281Z
paper_authors._id: 64ca8e0a8a16b1748fe44f21
paper_authors.avatarUrl: /avatars/0b56a1634dcd562c6516f26b5e9cde14.svg
paper_authors.fullname: Hong-Xing "Koven" Yu
paper_authors.type: user
paper_authors.user: Koooven
paper_authors._id: 6502a153e9230a325e02309e
paper_authors.name: Sharon Zhang
paper_authors._id: 6502a153e9230a325e02309f
paper_authors.name: Maneesh Agrawala
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2023-09-14T07:49:03.843Z
paper_authors._id: 642bb3e44f379cdc3deb26cd
paper_authors.avatarUrl: /avatars/556e792f013bcbe3748d7c9c719070d8.svg
paper_authors.fullname: Maneesh Agrawala
paper_authors.type: user
paper_authors.user: magrawala
paper_authors._id: 6502a153e9230a325e0230a0
paper_authors.name: Jiajun Wu
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2023-09-14T07:49:25.150Z
paper_authors._id: 647b7b8345616c3de3627863
paper_authors.avatarUrl: /avatars/8196364bffed71086ba9a0a4a62027d3.svg
paper_authors.fullname: Jiajun Wu
paper_authors.type: user
paper_authors.user: jiajunwu
paper_title: Tree-Structured Shading Decomposition
paper_summary: We study inferring a tree-structured representation from a single image for
  object shading. Prior work typically uses the parametric or measured
  representation to model shading, which is neither interpretable nor easily
  editable. We propose using the shade tree representation, which combines basic
  shading nodes and compositing methods to factorize object surface shading. The
  shade tree representation enables novice users who are unfamiliar with the
  physical shading process to edit object shading in an efficient and intuitive
  manner. A main challenge in inferring the shade tree is that the inference
  problem involves both the discrete tree structure and the continuous parameters
  of the tree nodes. We propose a hybrid approach to address this issue. We
  introduce an auto-regressive inference model to generate a rough estimation of
  the tree structure and node parameters, and then we fine-tune the inferred
  shade tree through an optimization algorithm. We show experiments on synthetic
  images, captured reflectance, real images, and non-realistic vector drawings,
  allowing downstream applications such as material editing, vectorized shading,
  and relighting. Project website: https://chen-geng.com/inv-shade-trees
paper_ai_keywords: tree-structured representation shade tree representation shading nodes compositing methods inferring the shade tree discrete tree structure continuous parameters auto-regressive inference model optimization algorithm material editing vectorized shading relighting