114 citations · 146 across the 13 of their papers we have counts for
9 papers · 1 filter
Octrees as an Explicit 3D Language
Ran Dan, Si-Tong Wei, Pengfei Xiong +3
Existing 3D large language models (LLMs) compromise on two fronts: they compress shapes into latent codebook indices or coordinate text, which removes spatial structure from what t…
CVT-GS: Learning to Simplify 3D Gaussian Splatting with Centroidal Voronoi Tessellation
Bingxian Li, Yilong Li, Jingliang Peng +6
While 3D Gaussian Splatting (3DGS) has emerged as a powerful representation for real-time novel view synthesis, rendering high-fidelity scenes often relies on a massive number of G…
ViSculpt: Visual-Centric Agentic Geometry Editing
Bo Pang, Jiaqi Pan, Xiaocheng Zhang +3
3D geometry editing is a critical yet labor-intensive part of the graphics pipeline, requiring artists to translate creative intent into precise operations in complex professional…
StateFlow: Building, Evolving, and Accessing 3D World States for Previsualization
Yuyang Yin, Zixiang Li, Longxuan Deng +11
Previsualization is an intermediate layer between ideas and production in film, games, architecture, and urban design. It lets creators iteratively refine scenes, actions, cameras,…
OctFusion: Octree-based Diffusion Models for 3D Shape Generation
Bojun Xiong, Si-Tong Wei, Xin-Yang Zheng +3
Diffusion models have emerged as a popular method for 3D generation. However, it is still challenging for diffusion models to efficiently generate diverse and high-quality 3D shape…
SinMPI: Novel View Synthesis from a Single Image with Expanded Multiplane Images
Guo Pu, Peng-Shuai Wang, Zhouhui Lian
Single-image novel view synthesis is a challenging and ongoing problem that aims to generate an infinite number of consistent views from a single input image. Although significant…
Point Transformer V3: Simpler, Faster, Stronger
Xiaoyang Wu, Li Jiang, Peng-Shuai Wang +6
This paper is not motivated to seek innovation within the attention mechanism. Instead, it focuses on overcoming the existing trade-offs between accuracy and efficiency within the…
Learning the Geodesic Embedding with Graph Neural Networks
Bo Pang, Zhongtian Zheng, Guoping Wang +1
We present GeGnn, a learning-based method for computing the approximate geodesic distance between two arbitrary points on discrete polyhedra surfaces with constant time complexity…
OctFormer: Octree-based Transformers for 3D Point Clouds
Peng-Shuai Wang
We propose octree-based transformers, named OctFormer, for 3D point cloud learning. OctFormer can not only serve as a general and effective backbone for 3D point cloud segmentation…