665 citations · 1k across the 35 of their papers we have counts for
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ConDaFormer: Disassembled Transformer with Local Structure Enhancement for 3D Point Cloud Understanding
Lunhao Duan, Shanshan Zhao, Nan Xue +3
Transformers have been recently explored for 3D point cloud understanding with impressive progress achieved. A large number of points, over 0.1 million, make the global self-attent…
Patched Line Segment Learning for Vector Road Mapping
Jiakun Xu, Bowen Xu, Gui-Song Xia +2
This paper presents a novel approach to computing vector road maps from satellite remotely sensed images, building upon a well-defined Patched Line Segment (PaLiS) representation f…
NEAT: Distilling 3D Wireframes from Neural Attraction Fields
Nan Xue, Bin Tan, Yuxi Xiao +4
This paper studies the problem of structured 3D reconstruction using wireframes that consist of line segments and junctions, focusing on the computation of structured boundary geom…
Depth and DOF Cues Make A Better Defocus Blur Detector
Yuxin Jin, Ming Qian, Jincheng Xiong +2
Defocus blur detection (DBD) separates in-focus and out-of-focus regions in an image. Previous approaches mistakenly mistook homogeneous areas in focus for defocus blur regions, li…
HGFormer: Hierarchical Grouping Transformer for Domain Generalized Semantic Segmentation
Jian Ding, Nan Xue, Gui-Song Xia +2
Current semantic segmentation models have achieved great success under the independent and identically distributed (i.i.d.) condition. However, in real-world applications, test dat…
Monocular 3D Object Detection with Bounding Box Denoising in 3D by Perceiver
Xianpeng Liu, Ce Zheng, Kelvin Cheng +3
The main challenge of monocular 3D object detection is the accurate localization of 3D center. Motivated by a new and strong observation that this challenge can be remedied by a 3D…
Sat2Density: Faithful Density Learning from Satellite-Ground Image Pairs
Ming Qian, Jincheng Xiong, Gui-Song Xia +1
This paper aims to develop an accurate 3D geometry representation of satellite images using satellite-ground image pairs. Our focus is on the challenging problem of 3D-aware ground…