4 papers
Instruct-Particulate: Scaling Feed-Forward 3D Object Articulation with Kinematic Control
Ruining Li, Yuxin Yao, Matt Zhou +5
Reconstructing articulated 3D objects is important for animation, gaming, and robotic simulations. Recent neural networks can estimate the articulated structure of 3D objects, but…
Articraft: An Agentic System for Scalable Articulated 3D Asset Generation
Matt Zhou, Ruining Li, Xiaoyang Lyu +6
A bottleneck in learning to understand articulated 3D objects is the lack of large and diverse datasets. In this paper, we propose to leverage large language models (LLMs) to close…
The Scene Language: Representing Scenes with Programs, Words, and Embeddings
Yunzhi Zhang, Zizhang Li, Matt Zhou +2
We introduce the Scene Language, a visual scene representation that concisely and precisely describes the structure, semantics, and identity of visual scenes. It represents a scene…
Variable Length Embeddings
Johnathan Chiu, Andi Gu, Matt Zhou
In this work, we introduce a novel deep learning architecture, Variable Length Embeddings (VLEs), an autoregressive model that can produce a latent representation composed of an ar…