Generative AI tools can provide people with the ability to create virtual environments and
scenes with natural language prompts. Yet, how people will formulate such prompts is …

Artificial intelligence (AI) methods are poised to revolutionize intellectual work, with
generative AI enabling automation of text analysis, text generation, and simple decision …

Autoregressive modeling has been a huge success in the field of natural language
processing (NLP). Recently, autoregressive models have emerged as a significant area of …

Autoregressive models have demonstrated great performance in natural language
processing (NLP) with impressive scalability, adaptability and generalizability. Inspired by …

The idea of 3D reconstruction as scene understanding is foundational in computer vision.
Reconstructing 3D scenes from 2D visual observations requires strong priors to …

We generate abstractions of buildings, reflecting the essential aspects of their geometry and
structure, by learning to invert procedural models. We first build a dataset of abstract …

Procedural Content Generation (PCG) is powerful in creating high-quality 3D contents, yet
controlling it to produce desired shapes is difficult and often requires extensive parameter …

The 3D reconstruction of construction sites is of great importance for construction progress,
quality, and safety management. Currently, most of the existing 3D reconstruction methods …

Open-universe 3D layout generation arranges unlabeled 3D assets conditioned on
language instruction. Large language models (LLMs) struggle with generating physically …

The promise of unsupervised multi-view-stereo (MVS) is to leverage large unlabeled
datasets, yet current methods underperform when training on difficult data, such as …