2 citations · 2 across the 6 of their papers we have counts for
5 papers · 1 filter
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…
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…