1 code implementation • 3 Mar 2024 • Yujie Lu, Long Wan, Nayu Ding, Yulong Wang, Shuhan Shen, Shen Cai, Lin Gao
However, common distance field based implicit representations, specifically signed distance field (SDF) for watertight shapes or unsigned distance field (UDF) for arbitrary shapes, routinely suffer from degradation of reconstruction accuracy when converting to explicit surface points and meshes.
1 code implementation • 28 Feb 2024 • Shen Cai, Zhanhao Wu, Lingxi Guo, Jiachun Wang, Siyu Zhang, Junchi Yan, Shuhan Shen
Under the minimal $4$-point configuration, the first and the last similarity transformations in SKS are computed by two anchor points on target and source planes, respectively.
1 code implementation • 27 Feb 2022 • Yongdong Huang, Yuanzhan Li, Xulong Cao, Siyu Zhang, Shen Cai, Ting Lu, Jie Wang, Yuqi Liu
However, many previous works employ neural networks with fixed architecture and size to represent different 3D objects, which lead to excessive network parameters for simple objects and limited reconstruction accuracy for complex objects.
1 code implementation • 19 Jan 2022 • Yuanzhan Li, Yuqi Liu, Yujie Lu, Siyu Zhang, Shen Cai, Yanting Zhang
Compared to previous works, our method achieves the high-fidelity and high-compression 3D object coding and reconstruction.
1 code implementation • 31 May 2021 • Siyu Zhang, Hui Cao, Yuqi Liu, Shen Cai, Yanting Zhang, Yuanzhan Li, Xiaoyu Chi
Using deep learning techniques to process 3D objects has achieved many successes.
no code implementations • 11 Jan 2021 • Yuqi Liu, Yin Wang, Haikuan Du, Shen Cai
To this end, the proposed method first uses local structured sampling methods such as HEALPix to construct a transformer grid by using the information of spherical points and its adjacent points, and then transforms the spherical signals to the vectors through the grid.
1 code implementation • 9 Nov 2020 • Ji Luo, Hui Cao, Jie Wang, Siyu Zhang, Shen Cai
Voxel-based 3D object classification has been thoroughly studied in recent years.
1 code implementation • 25 Dec 2019 • Hui Cao, Haikuan Du, Siyu Zhang, Shen Cai
Unlike previous methods that use points, voxels, or multi-view images as inputs of deep neural network (DNN), the proposed method constructs a class of more representative features named infilling spheres from signed distance field (SDF).