no code implementations • 6 Nov 2018 • Xinhai Liu, Zhizhong Han, Yu-Shen Liu, Matthias Zwicker
However, it is hard to capture fine-grained contextual information in hand-crafted or explicit manners, such as the correlation between different areas in a local region, which limits the discriminative ability of learned features.
Ranked #48 on 3D Part Segmentation on ShapeNet-Part
no code implementations • 18 May 2019 • Zhizhong Han, Xinhai Liu, Yu-Shen Liu, Matthias Zwicker
In contrast, we propose a deep neural network, called Parts4Feature, to learn 3D global features from part-level information in multiple views.
no code implementations • 2 Aug 2019 • Xinhai Liu, Zhizhong Han, Xin Wen, Yu-Shen Liu, Matthias Zwicker
Specifically, L2G-AE employs an encoder to encode the geometry information of multiple scales in a local region at the same time.
no code implementations • 29 Aug 2019 • Xin Wen, Zhizhong Han, Xinhai Liu, Yu-Shen Liu
Compared to the previous capsule network based methods, the feature routing on the spatial-aware capsules can learn more discriminative spatial relationships among local regions for point clouds, which establishes a direct mapping between log priors and the spatial locations through feature clusters.
no code implementations • 18 Mar 2020 • Xinhai Liu, Zhizhong Han, Fangzhou Hong, Yu-Shen Liu, Matthias Zwicker
However, due to the irregularity and sparsity in sampled point clouds, it is hard to encode the fine-grained geometry of local regions and their spatial relationships when only using the fixed-size filters and individual local feature integration, which limit the ability to learn discriminative features.
no code implementations • 10 May 2023 • Xinhai Liu, Zhizhong Han, Sanghuk Lee, Yan-Pei Cao, Yu-Shen Liu
Most of early methods selected the important points on 3D shapes by analyzing the intrinsic geometric properties of every single shape, which fails to capture the importance of points that distinguishes a shape from objects of other classes, i. e., the distinction of points.
1 code implementation • 8 Dec 2020 • Xinhai Liu, Xinchen Liu, Yu-Shen Liu, Zhizhong Han
The task of point cloud upsampling aims to acquire dense and uniform point sets from sparse and irregular point sets.
1 code implementation • 26 May 2020 • Xinhai Liu, Zhizhong Han, Yu-Shen Liu, Matthias Zwicker
According to our experiments under this fine-grained dataset, we find that state-of-the-art methods are significantly limited by the small variance among subcategories in the same category.