251 citations · 977 across the 32 of their papers we have counts for
7 papers · 1 filter
UrbanBIS: a Large-scale Benchmark for Fine-grained Urban Building Instance Segmentation
Guoqing Yang, Fuyou Xue, Qi Zhang +3
We present the UrbanBIS benchmark for large-scale 3D urban understanding, supporting practical urban-level semantic and building-level instance segmentation. UrbanBIS comprises six…
Learning Reconstructability for Drone Aerial Path Planning
Yilin Liu, Liqiang Lin, Yue Hu +4
We introduce the first learning-based reconstructability predictor to improve view and path planning for large-scale 3D urban scene acquisition using unmanned drones. In contrast t…
Photo-to-Shape Material Transfer for Diverse Structures
Ruizhen Hu, Xiangyu Su, Xiangkai Chen +2
We introduce a method for assigning photorealistic relightable materials to 3D shapes in an automatic manner. Our method takes as input a photo exemplar of a real object and a 3D o…
Differentiable Refraction-Tracing for Mesh Reconstruction of Transparent Objects
Jiahui Lyu, Bojian Wu, Dani Lischinski +2
Capturing the 3D geometry of transparent objects is a challenging task, ill-suited for general-purpose scanning and reconstruction techniques, since these cannot handle specular li…
SAGNet:Structure-aware Generative Network for 3D-Shape Modeling
Zhijie Wu, Xiang Wang, Di Lin +3
We present SAGNet, a structure-aware generative model for 3D shapes. Given a set of segmented objects of a certain class, the geometry of their parts and the pairwise relationships…
Non-Stationary Texture Synthesis by Adversarial Expansion
Yang Zhou, Zhen Zhu, Xiang Bai +3
The real world exhibits an abundance of non-stationary textures. Examples include textures with large-scale structures, as well as spatially variant and inhomogeneous textures. Whi…
P2P-NET: Bidirectional Point Displacement Net for Shape Transform
Kangxue Yin, Hui Huang, Daniel Cohen-Or +1
We introduce P2P-NET, a general-purpose deep neural network which learns geometric transformations between point-based shape representations from two domains, e.g., meso-skeletons…