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Books and Theses
- 2016
[b1]Daniel Ritchie:
Probabilistic programming for procedural modeling and design. Stanford University, USA, 2016
Journal Articles
- 2024
- [j21]Yuanbo Li
, Tianyi Ma, Zaineb Aljumayaat, Daniel Ritchie:
PossibleImpossibles: Exploratory Procedural Design of Impossible Structures. Comput. Graph. Forum 43(2): i-iii (2024) - [j20]Xiao Zhan, Rao Fu, Daniel Ritchie:
CharacterMixer: Rig-Aware Interpolation of 3D Characters. Comput. Graph. Forum 43(2): i-iii (2024) - [j19]Arman Maesumi, Dylan Hu, Krishi Saripalli, Vladimir G. Kim, Matthew Fisher, Sören Pirk, Daniel Ritchie:
One Noise to Rule Them All: Learning a Unified Model of Spatially-Varying Noise Patterns. ACM Trans. Graph. 43(4): 114:1-114:21 (2024) - 2023
- [j18]Daniel Ritchie, Paul Guerrero, R. Kenny Jones, Niloy J. Mitra, Adriana Schulz, Karl D. D. Willis, Jiajun Wu:
Neurosymbolic Models for Computer Graphics. Comput. Graph. Forum 42(2): 545-568 (2023) - [j17]R. Kenny Jones, Paul Guerrero, Niloy J. Mitra, Daniel Ritchie:
ShapeCoder: Discovering Abstractions for Visual Programs from Unstructured Primitives. ACM Trans. Graph. 42(4): 49:1-49:17 (2023) - [j16]Sharon Zhang, Jiaju Ma, Jiajun Wu, Daniel Ritchie, Maneesh Agrawala:
Editing Motion Graphics Video via Motion Vectorization and Transformation. ACM Trans. Graph. 42(6): 229:1-229:13 (2023) - 2022
- [j15]R. Kenny Jones, Aalia Habib, Daniel Ritchie:
SHRED: 3D Shape Region Decomposition with Learned Local Operations. ACM Trans. Graph. 41(6): 186:1-186:11 (2022) - 2021
- [j14]Kai Wang, Xianghao Xu, Leon Lei, Selena Ling, Natalie Lindsay, Angel X. Chang, Manolis Savva, Daniel Ritchie:
Roominoes: Generating Novel 3D Floor Plans From Existing 3D Rooms. Comput. Graph. Forum 40(5): 57-69 (2021) - [j13]R. Kenny Jones, David Charatan, Paul Guerrero, Niloy J. Mitra, Daniel Ritchie:
ShapeMOD: macro operation discovery for 3D shape programs. ACM Trans. Graph. 40(4): 153:1-153:16 (2021) - 2020
- [j12]Siddhartha Chaudhuri, Daniel Ritchie, Jiajun Wu, Kai Xu, Hao (Richard) Zhang:
Learning Generative Models of 3D Structures. Comput. Graph. Forum 39(2): 643-666 (2020) - [j11]R. Kenny Jones, Theresa Barton, Xianghao Xu, Kai Wang, Ellen Jiang, Paul Guerrero, Niloy J. Mitra, Daniel Ritchie:
ShapeAssembly: learning to generate programs for 3D shape structure synthesis. ACM Trans. Graph. 39(6): 234:1-234:20 (2020) - 2019
- [j10]Yifan Liu, Ruolan Tang, Daniel Ritchie:
Learning Style Compatibility Between Objects in a Real-World 3D Asset Database. Comput. Graph. Forum 38(7): 775-784 (2019) - [j9]Kai Wang, Yu-An Lin, Ben Weissmann, Manolis Savva, Angel X. Chang, Daniel Ritchie:
PlanIT: planning and instantiating indoor scenes with relation graph and spatial prior networks. ACM Trans. Graph. 38(4): 132:1-132:15 (2019) - 2018
- [j8]Daniel Ritchie, Sarah Jobalia, Anna Thomas:
Example-based Authoring of Procedural Modeling Programs with Structural and Continuous Variability. Comput. Graph. Forum 37(2): 401-413 (2018) - [j7]Kai Wang, Manolis Savva, Angel X. Chang, Daniel Ritchie:
Deep convolutional priors for indoor scene synthesis. ACM Trans. Graph. 37(4): 70 (2018) - 2015
- [j6]Daniel Ritchie, Sharon Lin, Noah D. Goodman, Pat Hanrahan:
Generating Design Suggestions under Tight Constraints with Gradient-based Probabilistic Programming. Comput. Graph. Forum 34(2): 515-526 (2015) - [j5]Daniel Ritchie, Ben Mildenhall, Noah D. Goodman, Pat Hanrahan:
Controlling procedural modeling programs with stochastically-ordered sequential Monte Carlo. ACM Trans. Graph. 34(4): 105:1-105:11 (2015) - 2013
- [j4]Sharon Lin, Daniel Ritchie, Matthew Fisher, Pat Hanrahan:
Probabilistic color-by-numbers: suggesting pattern colorizations using factor graphs. ACM Trans. Graph. 32(4): 37:1-37:12 (2013) - 2012
- [j3]Matthew Fisher, Daniel Ritchie, Manolis Savva, Thomas A. Funkhouser, Pat Hanrahan:
Example-based synthesis of 3D object arrangements. ACM Trans. Graph. 31(6): 135:1-135:11 (2012) - 2010
- [j2]Martin Wicke, Daniel Ritchie, Bryan Matthew Klingner, Sebastian Burke, Jonathan Richard Shewchuk, James F. O'Brien:
Dynamic local remeshing for elastoplastic simulation. ACM Trans. Graph. 29(4): 49:1-49:11 (2010) - 2009
- [j1]Nuttapong Chentanez, Ron Alterovitz, Daniel Ritchie, Lita Cho, Kris K. Hauser, Kenneth Y. Goldberg, Jonathan Richard Shewchuk, James F. O'Brien:
Interactive simulation of surgical needle insertion and steering. ACM Trans. Graph. 28(3): 88 (2009)
Conference and Workshop Papers
- 2024
- [c28]Qirui Wu, Daniel Ritchie, Manolis Savva, Angel X. Chang:
Generalizing Single-View 3D Shape Retrieval to Occlusions and Unseen Objects. 3DV 2024: 893-902 - [c27]R. Kenny Jones, Siddhartha Chaudhuri, Daniel Ritchie:
Learning to Infer Generative Template Programs for Visual Concepts. ICML 2024 - 2023
- [c26]Xianghao Xu, Paul Guerrero, Matthew Fisher, Siddhartha Chaudhuri, Daniel Ritchie:
Unsupervised 3D Shape Reconstruction by Part Retrieval and Assembly. CVPR 2023: 8559-8567 - [c25]Aditya Sanghi, Rao Fu, Vivian Liu, Karl D. D. Willis, Hooman Shayani, Amir Hosein Khasahmadi, Srinath Sridhar, Daniel Ritchie:
CLIP-Sculptor: Zero-Shot Generation of High-Fidelity and Diverse Shapes from Natural Language. CVPR 2023: 18339-18348 - [c24]Aditya Ganeshan, R. Kenny Jones, Daniel Ritchie:
Improving Unsupervised Visual Program Inference with Code Rewriting Families. ICCV 2023: 15745-15755 - [c23]Arman Maesumi, Paul Guerrero, Noam Aigerman, Vladimir G. Kim, Matthew Fisher, Siddhartha Chaudhuri, Daniel Ritchie:
Explorable Mesh Deformation Subspaces from Unstructured 3D Generative Models. SIGGRAPH Asia 2023: 68:1-68:11 - 2022
- [c22]Ying Xu, Dakuo Wang, Mo Yu, Daniel Ritchie, Bingsheng Yao, Tongshuang Wu, Zheng Zhang, Toby Jia-Jun Li, Nora Bradford, Branda Sun, Tran Bao Hoang, Yisi Sang, Yufang Hou, Xiaojuan Ma, Diyi Yang, Nanyun Peng, Zhou Yu, Mark Warschauer:
Fantastic Questions and Where to Find Them: FairytaleQA - An Authentic Dataset for Narrative Comprehension. ACL (1) 2022: 447-460 - [c21]Zheng Zhang, Ying Xu, Yanhao Wang, Bingsheng Yao, Daniel Ritchie, Tongshuang Wu, Mo Yu, Dakuo Wang, Toby Jia-Jun Li:
StoryBuddy: A Human-AI Collaborative Chatbot for Parent-Child Interactive Storytelling with Flexible Parental Involvement. CHI 2022: 218:1-218:21 - [c20]R. Kenny Jones, Homer Walke, Daniel Ritchie:
PLAD: Learning to Infer Shape Programs with Pseudo-Labels and Approximate Distributions. CVPR 2022: 9861-9870 - [c19]R. Kenny Jones, Aalia Habib, Rana Hanocka, Daniel Ritchie:
The Neurally-Guided Shape Parser: Grammar-based Labeling of 3D Shape Regions with Approximate Inference. CVPR 2022: 11604-11613 - [c18]Kai Wang, Paul Guerrero, Vladimir G. Kim, Siddhartha Chaudhuri, Minhyuk Sung, Daniel Ritchie:
The Shape Part Slot Machine: Contact-Based Reasoning for Generating 3D Shapes from Parts. ECCV (3) 2022: 610-626 - [c17]Hameed Abdul-Rashid, Miles Freeman, Ben Abbatematteo, George Konidaris, Daniel Ritchie:
Learning to Infer Kinematic Hierarchies for Novel Object Instances. ICRA 2022: 8461-8467 - [c16]Rao Fu, Xiao Zhan, Yiwen Chen, Daniel Ritchie, Srinath Sridhar:
ShapeCrafter: A Recursive Text-Conditioned 3D Shape Generation Model. NeurIPS 2022 - [c15]Xianghao Xu, Yifan Ruan, Srinath Sridhar, Daniel Ritchie:
Unsupervised Kinematic Motion Detection for Part-segmented 3D Shape Collections. SIGGRAPH (Conference Paper Track) 2022: 2:1-2:9 - 2021
- [c14]Xianghao Xu, Wenzhe Peng, Chin-Yi Cheng, Karl D. D. Willis, Daniel Ritchie:
Inferring CAD Modeling Sequences Using Zone Graphs. CVPR 2021: 6062-6070 - 2020
- [c13]Xianghao Xu, David Charatan, Sonia Raychaudhuri, Hanxiao Jiang, Mae Heitmann, Vladimir G. Kim, Siddhartha Chaudhuri, Manolis Savva, Angel X. Chang, Daniel Ritchie:
Motion Annotation Programs: A Scalable Approach to Annotating Kinematic Articulations in Large 3D Shape Collections. 3DV 2020: 613-622 - [c12]Purvi Goel, Loudon Cohen, James Guesman, Vikas Thamizharasan, James Tompkin, Daniel Ritchie:
Shape from Tracing: Towards Reconstructing 3D Object Geometry and SVBRDF Material from Images via Differentiable Path Tracing. 3DV 2020: 1186-1195 - [c11]Wallace P. Lira, Johannes Merz, Daniel Ritchie, Daniel Cohen-Or, Hao (Richard) Zhang:
GANHopper: Multi-hop GAN for Unsupervised Image-to-Image Translation. ECCV (26) 2020: 363-379 - 2019
- [c10]Daniel Ritchie, Kai Wang, Yu-An Lin:
Fast and Flexible Indoor Scene Synthesis via Deep Convolutional Generative Models. CVPR 2019: 6182-6190 - [c9]Siddhartha Chaudhuri, Daniel Ritchie, Kai Xu, Hao (Richard) Zhang:
Learning Generative Models of 3D Structures. Eurographics (Tutorials) 2019: 47-51 - [c8]Yunchao Liu, Zheng Wu, Daniel Ritchie, William T. Freeman, Joshua B. Tenenbaum, Jiajun Wu:
Learning to Describe Scenes with Programs. ICLR (Poster) 2019 - 2018
- [c7]Angela Dai, Daniel Ritchie, Martin Bokeloh, Scott Reed, Jürgen Sturm, Matthias Nießner:
ScanComplete: Large-Scale Scene Completion and Semantic Segmentation for 3D Scans. CVPR 2018: 4578-4587 - [c6]Aaron Gokaslan, Vivek Ramanujan, Daniel Ritchie, Kwang In Kim, James Tompkin:
Improving Shape Deformation in Unsupervised Image-to-Image Translation. ECCV (12) 2018: 662-678 - [c5]Kevin Ellis, Daniel Ritchie, Armando Solar-Lezama, Josh Tenenbaum:
Learning to Infer Graphics Programs from Hand-Drawn Images. NeurIPS 2018: 6062-6071 - 2016
- [c4]Daniel Ritchie, Andreas Stuhlmüller, Noah D. Goodman:
C3: Lightweight Incrementalized MCMC for Probabilistic Programs using Continuations and Callsite Caching. AISTATS 2016: 28-37 - [c3]Daniel Ritchie, Anna Thomas, Pat Hanrahan, Noah D. Goodman:
Neurally-Guided Procedural Models: Amortized Inference for Procedural Graphics Programs using Neural Networks. NIPS 2016: 622-630 - 2014
- [c2]Zachary DeVito, Daniel Ritchie, Matthew Fisher, Alex Aiken, Pat Hanrahan:
First-class runtime generation of high-performance types using exotypes. PLDI 2014: 77-88 - 2011
- [c1]Daniel Ritchie, Ankita Arvind Kejriwal, Scott R. Klemmer:
d.tour: style-based exploration of design example galleries. UIST 2011: 165-174
Informal and Other Publications
- 2024
- [i40]Qirui Wu, Daniel Ritchie, Manolis Savva, Angel X. Chang:
Generalizing Single-View 3D Shape Retrieval to Occlusions and Unseen Objects. CoRR abs/2401.00405 (2024) - [i39]Xiao Zhan, Rao Fu, Daniel Ritchie:
CharacterMixer: Rig-Aware Interpolation of 3D Characters. CoRR abs/2402.15580 (2024) - [i38]Rio Aguina-Kang, Maxim Gumin, Do Heon Han, Stewart Morris, Seung Jean Yoo, Aditya Ganeshan, R. Kenny Jones, Qiuhong Anna Wei, Kailiang Fu, Daniel Ritchie:
Open-Universe Indoor Scene Generation using LLM Program Synthesis and Uncurated Object Databases. CoRR abs/2403.09675 (2024) - [i37]Qirui Wu, Sonia Raychaudhuri, Daniel Ritchie, Manolis Savva, Angel X. Chang:
R3DS: Reality-linked 3D Scenes for Panoramic Scene Understanding. CoRR abs/2403.12301 (2024) - [i36]R. Kenny Jones, Siddhartha Chaudhuri, Daniel Ritchie:
Learning to Infer Generative Template Programs for Visual Concepts. CoRR abs/2403.15476 (2024) - [i35]Arman Maesumi, Dylan Hu, Krishi Saripalli, Vladimir G. Kim, Matthew Fisher, Sören Pirk, Daniel Ritchie:
One Noise to Rule Them All: Learning a Unified Model of Spatially-Varying Noise Patterns. CoRR abs/2404.16292 (2024) - [i34]Xianghao Xu, Aditya Ganeshan, Karl D. D. Willis, Yewen Pu, Daniel Ritchie:
Creating Language-driven Spatial Variations of Icon Images. CoRR abs/2405.19636 (2024) - [i33]Aditya Ganeshan, Ryan Y. Huang, Xianghao Xu, R. Kenny Jones, Daniel Ritchie:
ParSEL: Parameterized Shape Editing with Language. CoRR abs/2405.20319 (2024) - [i32]R. Kenny Jones, Renhao Zhang, Aditya Ganeshan, Daniel Ritchie:
Learning to Edit Visual Programs with Self-Supervision. CoRR abs/2406.02383 (2024) - 2023
- [i31]Xianghao Xu, Paul Guerrero, Matthew Fisher, Siddhartha Chaudhuri, Daniel Ritchie:
Unsupervised 3D Shape Reconstruction by Part Retrieval and Assembly. CoRR abs/2303.01999 (2023) - [i30]Daniel Ritchie, Paul Guerrero, R. Kenny Jones, Niloy J. Mitra, Adriana Schulz, Karl D. D. Willis, Jiajun Wu:
Neurosymbolic Models for Computer Graphics. CoRR abs/2304.10320 (2023) - [i29]R. Kenny Jones, Paul Guerrero, Niloy J. Mitra, Daniel Ritchie:
ShapeCoder: Discovering Abstractions for Visual Programs from Unstructured Primitives. CoRR abs/2305.05661 (2023) - [i28]Sharon Zhang, Jiaju Ma, Jiajun Wu, Daniel Ritchie, Maneesh Agrawala:
Editing Motion Graphics Video via Motion Vectorization and Transformation. CoRR abs/2309.14642 (2023) - [i27]Aditya Ganeshan, R. Kenny Jones, Daniel Ritchie:
Improving Unsupervised Visual Program Inference with Code Rewriting Families. CoRR abs/2309.14972 (2023) - [i26]Arman Maesumi, Paul Guerrero, Vladimir G. Kim, Matthew Fisher, Siddhartha Chaudhuri, Noam Aigerman, Daniel Ritchie:
Explorable Mesh Deformation Subspaces from Unstructured Generative Models. CoRR abs/2310.07814 (2023) - 2022
- [i25]Zheng Zhang, Ying Xu, Yanhao Wang, Bingsheng Yao, Daniel Ritchie, Tongshuang Wu, Mo Yu, Dakuo Wang, Toby Jia-Jun Li:
StoryBuddy: A Human-AI Collaborative Chatbot for Parent-Child Interactive Storytelling with Flexible Parental Involvement. CoRR abs/2202.06205 (2022) - [i24]Ying Xu, Dakuo Wang, Mo Yu, Daniel Ritchie, Bingsheng Yao, Tongshuang Wu, Zheng Zhang, Toby Jia-Jun Li, Nora Bradford, Branda Sun, Tran Bao Hoang, Yisi Sang, Yufang Hou, Xiaojuan Ma, Diyi Yang, Nanyun Peng, Zhou Yu, Mark Warschauer:
Fantastic Questions and Where to Find Them: FairytaleQA - An Authentic Dataset for Narrative Comprehension. CoRR abs/2203.13947 (2022) - [i23]R. Kenny Jones, Aalia Habib, Daniel Ritchie:
SHRED: 3D Shape Region Decomposition with Learned Local Operations. CoRR abs/2206.03480 (2022) - [i22]Xianghao Xu, Yifan Ruan, Srinath Sridhar, Daniel Ritchie:
Unsupervised Kinematic Motion Detection for Part-segmented 3D Shape Collections. CoRR abs/2206.08497 (2022) - [i21]Rao Fu, Xiao Zhan, Yiwen Chen, Daniel Ritchie, Srinath Sridhar:
ShapeCrafter: A Recursive Text-Conditioned 3D Shape Generation Model. CoRR abs/2207.09446 (2022) - [i20]Aditya Sanghi, Rao Fu, Vivian Liu, Karl D. D. Willis, Hooman Shayani, Amir Hosein Khasahmadi, Srinath Sridhar, Daniel Ritchie:
TextCraft: Zero-Shot Generation of High-Fidelity and Diverse Shapes from Text. CoRR abs/2211.01427 (2022) - 2021
- [i19]Xianghao Xu, Wenzhe Peng, Chin-Yi Cheng, Karl D. D. Willis, Daniel Ritchie:
Inferring CAD Modeling Sequences Using Zone Graphs. CoRR abs/2104.03900 (2021) - [i18]R. Kenny Jones, David Charatan, Paul Guerrero, Niloy J. Mitra, Daniel Ritchie:
ShapeMOD: Macro Operation Discovery for 3D Shape Programs. CoRR abs/2104.06392 (2021) - [i17]R. Kenny Jones, Rana Hanocka, Daniel Ritchie:
The Neurally-Guided Shape Parser: A Monte Carlo Method for Hierarchical Labeling of Over-segmented 3D Shapes. CoRR abs/2106.12026 (2021) - [i16]Hameed Abdul-Rashid, Miles Freeman, Ben Abbatematteo, George Dimitri Konidaris, Daniel Ritchie:
Learning to Infer Kinematic Hierarchies for Novel Object Instances. CoRR abs/2110.07911 (2021) - [i15]Kai Wang, Paul Guerrero, Vladimir G. Kim, Siddhartha Chaudhuri, Minhyuk Sung, Daniel Ritchie:
The Shape Part Slot Machine: Contact-based Reasoning for Generating 3D Shapes from Parts. CoRR abs/2112.00584 (2021) - [i14]Kai Wang, Xianghao Xu, Leon Lei, Selena Ling, Natalie Lindsay, Angel X. Chang, Manolis Savva, Daniel Ritchie:
Roominoes: Generating Novel 3D Floor Plans From Existing 3D Rooms. CoRR abs/2112.05644 (2021) - [i13]Bryce Blinn, Alexander Ding, Daniel Ritchie, R. Kenny Jones, Srinath Sridhar, Manolis Savva:
Learning Body-Aware 3D Shape Generative Models. CoRR abs/2112.07022 (2021) - 2020
- [i12]Wallace P. Lira, Johannes Merz, Daniel Ritchie, Daniel Cohen-Or, Hao (Richard) Zhang:
GANHopper: Multi-Hop GAN for Unsupervised Image-to-Image Translation. CoRR abs/2002.10102 (2020) - [i11]R. Kenny Jones, Theresa Barton, Xianghao Xu, Kai Wang, Ellen Jiang, Paul Guerrero, Niloy J. Mitra, Daniel Ritchie:
ShapeAssembly: Learning to Generate Programs for 3D Shape Structure Synthesis. CoRR abs/2009.08026 (2020) - [i10]Homer Walke, R. Kenny Jones, Daniel Ritchie:
Learning to Infer Shape Programs Using Latent Execution Self Training. CoRR abs/2011.13045 (2020) - [i9]Purvi Goel, Loudon Cohen, James Guesman, Vikas Thamizharasan, James Tompkin, Daniel Ritchie:
Shape From Tracing: Towards Reconstructing 3D Object Geometry and SVBRDF Material from Images via Differentiable Path Tracing. CoRR abs/2012.03939 (2020) - 2018
- [i8]Aaron Gokaslan, Vivek Ramanujan, Daniel Ritchie, Kwang In Kim, James Tompkin:
Improving Shape Deformation in Unsupervised Image-to-Image Translation. CoRR abs/1808.04325 (2018) - [i7]Daniel Ritchie, Kai Wang, Yu-An Lin:
Fast and Flexible Indoor Scene Synthesis via Deep Convolutional Generative Models. CoRR abs/1811.12463 (2018) - 2017
- [i6]Kevin Ellis, Daniel Ritchie, Armando Solar-Lezama, Joshua B. Tenenbaum:
Learning to Infer Graphics Programs from Hand-Drawn Images. CoRR abs/1707.09627 (2017) - [i5]Maxime Voisin, Daniel Ritchie:
An Improved Training Procedure for Neural Autoregressive Data Completion. CoRR abs/1711.08598 (2017) - [i4]Angela Dai, Daniel Ritchie, Martin Bokeloh, Scott Reed, Jürgen Sturm, Matthias Nießner:
ScanComplete: Large-Scale Scene Completion and Semantic Segmentation for 3D Scans. CoRR abs/1712.10215 (2017) - 2016
- [i3]Daniel Ritchie, Anna Thomas, Pat Hanrahan, Noah D. Goodman:
Neurally-Guided Procedural Models: Learning to Guide Procedural Models with Deep Neural Networks. CoRR abs/1603.06143 (2016) - [i2]Daniel Ritchie, Paul Horsfall, Noah D. Goodman:
Deep Amortized Inference for Probabilistic Programs. CoRR abs/1610.05735 (2016) - 2015
- [i1]Daniel Ritchie, Andreas Stuhlmüller, Noah D. Goodman:
C3: Lightweight Incrementalized MCMC for Probabilistic Programs using Continuations and Callsite Caching. CoRR abs/1509.02151 (2015)
Coauthor Index
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