79 citations · 109 across the 13 of their papers we have counts for
6 papers · 1 filter
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…
PartComposer: Learning and Composing Part-Level Concepts from Single-Image Examples
Junyu Liu, R. Kenny Jones, Daniel Ritchie
We present PartComposer: a framework for part-level concept learning from single-image examples that enables text-to-image diffusion models to compose novel objects from meaningful…
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…
ShapeCoder: Discovering Abstractions for Visual Programs from Unstructured Primitives
R. Kenny Jones, Paul Guerrero, Niloy J. Mitra +1
Programs are an increasingly popular representation for visual data, exposing compact, interpretable structure that supports manipulation. Visual programs are usually written in do…
ShapeMOD: Macro Operation Discovery for 3D Shape Programs
R. Kenny Jones, David Charatan, Paul Guerrero +2
A popular way to create detailed yet easily controllable 3D shapes is via procedural modeling, i.e. generating geometry using programs. Such programs consist of a series of instruc…
ShapeAssembly: Learning to Generate Programs for 3D Shape Structure Synthesis
R. Kenny Jones, Theresa Barton, Xianghao Xu +5
Manually authoring 3D shapes is difficult and time consuming; generative models of 3D shapes offer compelling alternatives. Procedural representations are one such possibility: the…