131 citations · 185 across the 6 of their papers we have counts for
6 papers
From Orbit to Ground: Generative City Photogrammetry from Extreme Off-Nadir Satellite Images
Fei Yu, Yu Liu, Luyang Tang +10
City-scale 3D reconstruction from satellite imagery presents the challenge of extreme viewpoint extrapolation, where our goal is to synthesize ground-level novel views from sparse…
PointCNN++: Performant Convolution on Native Points
Lihan Li, Haofeng Zhong, Rui Bu +4
Existing convolutional learning methods for 3D point cloud data are divided into two paradigms: point-based methods that preserve geometric precision but often face performance cha…
Value-State Gated Attention for Mitigating Extreme-Token Phenomena in Transformers
Rui Bu, Haofeng Zhong, Wenzheng Chen +1
Large models based on the Transformer architecture are susceptible to extreme-token phenomena, such as attention sinks and value-state drains. These issues, which degrade model per…
Mutual Information Maximization in Graph Neural Networks
Xinhan Di, Pengqian Yu, Rui Bu +1
A variety of graph neural networks (GNNs) frameworks for representation learning on graphs have been recently developed. These frameworks rely on aggregation and iteration scheme t…
PointCNN: Convolution On -Transformed Points
Yangyan Li, Rui Bu, Mingchao Sun +3
We present a simple and general framework for feature learning from point clouds. The key to the success of CNNs is the convolution operator that is capable of leveraging spatially…
Large-Scale 3D Shape Reconstruction and Segmentation from ShapeNet Core55
Li Yi, Lin Shao, Manolis Savva +47
We introduce a large-scale 3D shape understanding benchmark using data and annotation from ShapeNet 3D object database. The benchmark consists of two tasks: part-level segmentation…