2 citations · 2 across the 4 of their papers we have counts for
5 papers
NuiWorld: Exploring a Scalable Framework for End-to-End Controllable World Generation
Han-Hung Lee, Cheng-Yu Yang, Yu-Lun Liu +1
World generation is a fundamental capability for applications like video games, simulation, and robotics. However, existing approaches face three main obstacles: controllability, s…
NuiScene: Exploring Efficient Generation of Unbounded Outdoor Scenes
Han-Hung Lee, Qinghong Han, Angel X. Chang
In this paper, we explore the task of generating expansive outdoor scenes, ranging from castles to high-rises. Unlike indoor scene generation, which has been a primary focus of pri…
An Object is Worth 64x64 Pixels: Generating 3D Object via Image Diffusion
Xingguang Yan, Han-Hung Lee, Ziyu Wan +1
We introduce a new approach for generating realistic 3D models with UV maps through a representation termed "Object Images." This approach encapsulates surface geometry, appearance…
Duoduo CLIP: Efficient 3D Understanding with Multi-View Images
Han-Hung Lee, Yiming Zhang, Angel X. Chang
We introduce Duoduo CLIP, a model for 3D representation learning that learns shape encodings from multi-view images instead of point clouds. The choice of multi-view images allows…
Text-to-3D Shape Generation
Han-Hung Lee, Manolis Savva, Angel X. Chang
Recent years have seen an explosion of work and interest in text-to-3D shape generation. Much of the progress is driven by advances in 3D representations, large-scale pretraining a…