Oct 8, 2022 · Feedback connections between two adjacent time steps exploit fine-grained features to improve present shape generations. The main challenge of ...
To this end, we propose a novel Feedback Network (FBNet) for point cloud completion, in which present features are efficiently refined by rerouting subsequent ...
Nov 11, 2022 · We propose a novel feedback network (FBNet) for point completion, which recurrently refines completion shapes across time steps. To the best of ...
Oct 23, 2022 · Feedback connections between two adjacent time steps exploit fine-grained features to improve present shape generations. The main challenge of ...
The rapid development of point cloud learning has driven point cloud completion into a new era. However, the information flows of most existing completion ...
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FBNet: Feedback Network for Point Cloud Completion ... Authors: Xuejun Yan; Hongyu Yan; Jingjing Wang; Hang Du; Zhihong Wu; Di Xie; Shiliang Pu; Li Lu. List ...
HGNet. The hierarchical graph-based encoder stacks 3 EdgeConv and 2 AdaptGP layers. Both EdgeConv and AdaptGP use k-nearest neighbors (kNN) as the.
FBNet: Feedback Network for Point Cloud Completion. ECCV, 2022. Oral. Point Cloud Upsampling. Point Cloud Upsampling via Cascaded Refinement Network. ACCV ...
FBNet is a type of convolutional neural architectures discovered through DNAS neural architecture search. It utilises a basic type of image model block ...
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