1. SIGGRAPH Paper Reading 2011 Huang Haibin 2011.7.4

2. Paper list Procedural & Interactive Modeling  Interactive Furniture Layout Using Interior Design Guidelines  Converting 3D Furniture Models to Fabricatable Parts and Connectors  Make it Home: Automatic Optimization of Furniture Arrangement  Computer-Generated Residential Building Layouts  Interactive Architectural Modeling with Procedural Extrusions  Metropolis Procedural Modeling Image Processing  Domain Transform for Edge-Aware Image and Video Processing  Non-Rigid Dense Correspondence with Applications for Image Enhancement

3. Layout Generation Interactive Furniture Layout Using Interior Design Guidelines Computer-Generated Residential Building Layouts

4. Interactive Furniture Layout Using Interior Design Guidelines (SIGGRAPH 2011)

5. Paul Merrell Maneesh Agrawala Eric Schkufza Zeyang Li Stanford University Vladlen Koltun University of California, Berkeley

6. Main idea

8. Contributions 1. Identify and operationalize a set of design guidelines for furniture layout 2. Develop an interactive system for creating furniture arrangements based on these guidelines

9. Furniture Layout Guidelines 1. Functional Criteria 2.Visual Criteria 3. Authoring

10. Functional Criteria 1. Clearance 2. Circulation

11. 3. Pairwise relationships

12. 4.Conversation

13. Functional Criteria 1. Balance 2. Alignment

14. 3. Emphasis

16. Generation Suggestions Monte Carlo Sampler

17. Density Function and Sampling

18. Results

20. Computer-Generated Residential Building Layouts(SIGRAPH Asia 2010)

21. Paul Merrell Eric Schkufza Zeyang Li Stanford University

22. Main idea A list of high-level requirements Computer-Generated Residential Building Layouts

23. Contributions Data-driven generation of architectural programs from high-level requirements. Fully automated generation of detailed multi- story floor plans from architectural programs. An end-to-end approach to automated generation of building layouts from high-level requirements.

24. Building Layout Design 1. Architectural Programming 2.Floor Plan Optimization 3. Generating 3D models

25. Data- driven Architectural Programming 1. Bayesian Networks

26. Structure Learning

27. Floor Plan Optimization Proposal Moves 1.Notation 2.Sliding a wall 3.Swapping rooms

28. Cost Function Accessibility Dimensions Floors Shapes

30. Generating 3D models Passageways Windows Staircases Roofs

31. Results

32. Procedural & Interactive Modeling Interactive Architectural Modeling with Procedural Extrusions Metropolis Procedural Modeling

33. 1. Grammar-based: L-system… 2. Other: 3DMax…

34. Metropolis Procedural Modeling

36. Main Idea

37. Contribution An algorithm for controlling grammar-based procedural models

38. Solutions

39. Problems 1. Generate the space of productions from the grammar 2.Define an objective function that quantifies the similarity between a given production and the specification 3. Optimization

40. PROBABILISTIC INFERENCE FOR GRAMMARS

41. LIKELIHOOD FORMULATIONS Image- and volume-based modeling Mondrian modeling

42. Optimization MCMC  jump MCMC 1.Reversibility 2.Dimension matching 3Acceptance probability

43. MCMC FOR GRAMMARS Diffusion moves Jump moves

45. Results

48. Interactive Architectural Modeling with Procedural Extrusions

50. Main idea Model complex architectural features, including overhanging roofs, dormer windows, interior dormer windows, roof constructions with vertical walls, buttresses, chimneys, bay windows, columns, pilasters, and alcoves.

51. USER INTERFACE DESCRIPTION

52. Modeling With Profiles Plans and Profiles Overhangs Anchors Plan Edits Positioning Procedural Details

54. COMPUTING PROCEDURAL EXTRUSIONS Generalized Intersection Event Edge Direction Events Profile Offset Events Insertions into the Polygon Ambiguities in Procedural Extrusions

57. Image Processing Domain Transform for Edge-Aware Image and Video Processing Non-Rigid Dense Correspondence with Applications for Image Enhancement

58. Domain Transform for Edge-Aware Image and Video Processing

59. Authors

60. Main idea

62. Contributions

63. Transform for Edge-Preserving Filtering

65. 5D 2D 1D

66. Domain Transform

67. Application to Edge-Preserving Filtering

68. Filtering 2D Signals

69. Results

70. Detail Manipulation Tone Mapping Stylization Joint Filtering Colorization

73. Non-Rigid Dense Correspondence with Applications for Image Enhancement

74. Authors Yoav HaCohen Eli Shechtman Dan Goldman Dani Lischinski The Hebrew University of Jerusalem Adobe Systems

75. Main idea The images are close to each other in time and in viewpoint, and a dense correspondence field may be established using optical flow or stereo reconstruction techniques. The difference in viewpoint may be large, but the scene consists of mostly rigid objects

76. The input images share some common content, but may differ significantly due to a variety of factors, such as non-rigid changes in the scene, changes in lighting and tone mapping, and different cameras and lenses.

77. Overview

78. Nearest-neighbor search Based on Generalized PatchMatch algorithm(SIGGRAPH 2010)

79. Aggregating consistent regions

80. Global color mapping Search constraints

81. Evaluation

83. Applications Local color transfer Deblurring Mask transfer