2 citations · 2 across the 11 of their papers we have counts for
11 papers
Creative Robot Tool Use by Counterfactual Reasoning
M. Tuluhan Akbulut, Varun Satheesh, Ahmed Jaafar +5
We propose a causal reasoning framework for creative robot tool use where a suitable tool for a task is correctly identified for use beyond its primary objectives. The proposed fra…
Residual Primitive Fitting of 3D Shapes with SuperFrusta
Aditya Ganeshan, Matheus Gadelha, Thibault Groueix +6
We introduce a framework for converting 3D shapes into compact and editable assemblies of analytic primitives, directly addressing the persistent trade-off between reconstruction f…
Procedural Scene Programs for Open-Universe Scene Generation: LLM-Free Error Correction via Program Search
Maxim Gumin, Do Heon Han, Seung Jean Yoo +6
Synthesizing 3D scenes from open-vocabulary text descriptions is a challenging, important, and recently-popular application. One of its critical subproblems is layout generation: g…
MiGumi: Making Tightly Coupled Integral Joints Millable
Aditya Ganeshan, Kurt Fleischer, Wenzel Jakob +4
Traditional integral wood joints, despite their strength, durability, and elegance, remain rare in modern workflows due to the cost and difficulty of manual fabrication. CNC millin…
Imperative vs. Declarative Programming Paradigms for Open-Universe Scene Generation
Maxim Gumin, Do Heon Han, Seung Jean Yoo +5
Current methods for generating 3D scene layouts from text predominantly follow a declarative paradigm, where a Large Language Model (LLM) specifies high-level constraints that are…
Pattern Analogies: Learning to Perform Programmatic Image Edits by Analogy
Aditya Ganeshan, Thibault Groueix, Paul Guerrero +3
Pattern images are everywhere in the digital and physical worlds, and tools to edit them are valuable. But editing pattern images is tricky: desired edits are often programmatic: s…
Learning to Edit Visual Programs with Self-Supervision
R. Kenny Jones, Renhao Zhang, Aditya Ganeshan +1
We design a system that learns how to edit visual programs. Our edit network consumes a complete input program and a visual target. From this input, we task our network with predic…
ParSEL: Parameterized Shape Editing with Language
Aditya Ganeshan, Ryan Y. Huang, Xianghao Xu +2
The ability to edit 3D assets from natural language presents a compelling paradigm to aid in the democratization of 3D content creation. However, while natural language is often ef…
Creating Language-driven Spatial Variations of Icon Images
Xianghao Xu, Aditya Ganeshan, Karl D. D. Willis +2
Editing 2D icon images can require significant manual effort from designers. It involves manipulating multiple geometries while maintaining the logical or physical coherence of the…
Open-Universe Indoor Scene Generation using LLM Program Synthesis and Uncurated Object Databases
Rio Aguina-Kang, Maxim Gumin, Do Heon Han +7
We present a system for generating indoor scenes in response to text prompts. The prompts are not limited to a fixed vocabulary of scene descriptions, and the objects in generated…
Improving Unsupervised Visual Program Inference with Code Rewriting Families
Aditya Ganeshan, R. Kenny Jones, Daniel Ritchie
Programs offer compactness and structure that makes them an attractive representation for visual data. We explore how code rewriting can be used to improve systems for inferring pr…