665 citations · 1k across the 35 of their papers we have counts for
36 papers
Partial Distribution Matching via Partial Wasserstein Adversarial Networks
Zi-Ming Wang, Nan Xue, Ling Lei +2
This paper studies the problem of distribution matching (DM), which is a fundamental machine learning problem seeking to robustly align two probability distributions. Our approach…
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…
NOPE-SAC: Neural One-Plane RANSAC for Sparse-View Planar 3D Reconstruction
Bin Tan, Nan Xue, Tianfu Wu +1
This paper studies the challenging two-view 3D reconstruction in a rigorous sparse-view configuration, which is suffering from insufficient correspondences in the input image pairs…
Level-SfM: Structure from Motion on Neural Level Set of Implicit Surfaces
Yuxi Xiao, Nan Xue, Tianfu Wu +1
This paper presents a neural incremental Structure-from-Motion (SfM) approach, Level-SfM, which estimates the camera poses and scene geometry from a set of uncalibrated images…
Holistically-Attracted Wireframe Parsing: From Supervised to Self-Supervised Learning
Nan Xue, Tianfu Wu, Song Bai +4
This article presents Holistically-Attracted Wireframe Parsing (HAWP), a method for geometric analysis of 2D images containing wireframes formed by line segments and junctions. HAW…
HoW-3D: Holistic 3D Wireframe Perception from a Single Image
Wenchao Ma, Bin Tan, Nan Xue +3
This paper studies the problem of holistic 3D wireframe perception (HoW-3D), a new task of perceiving both the visible 3D wireframes and the invisible ones from single-view 2D imag…
Accurate Polygonal Mapping of Buildings in Satellite Imagery
Bowen Xu, Jiakun Xu, Nan Xue +1
This paper studies the problem of polygonal mapping of buildings by tackling the issue of mask reversibility that leads to a notable performance gap between the predicted masks and…
Revisiting Document Image Dewarping by Grid Regularization
Xiangwei Jiang, Rujiao Long, Nan Xue +3
This paper addresses the problem of document image dewarping, which aims at eliminating the geometric distortion in document images for document digitization. Instead of designing…
Partial Wasserstein Adversarial Network for Non-rigid Point Set Registration
Zi-Ming Wang, Nan Xue, Ling Lei +1
Given two point sets, the problem of registration is to recover a transformation that matches one set to the other. This task is challenging due to the presence of the large number…
Learning Auxiliary Monocular Contexts Helps Monocular 3D Object Detection
Xianpeng Liu, Nan Xue, Tianfu Wu
Monocular 3D object detection aims to localize 3D bounding boxes in an input single 2D image. It is a highly challenging problem and remains open, especially when no extra informat…
Decoupling Zero-Shot Semantic Segmentation
Jian Ding, Nan Xue, Gui-Song Xia +1
Zero-shot semantic segmentation (ZS3) aims to segment the novel categories that have not been seen in the training. Existing works formulate ZS3 as a pixel-level zeroshot classific…
LUAI Challenge 2021 on Learning to Understand Aerial Images
Gui-Song Xia, Jian Ding, Ming Qian +33
This report summarizes the results of Learning to Understand Aerial Images (LUAI) 2021 challenge held on ICCV 2021, which focuses on object detection and semantic segmentation in a…
Parsing Table Structures in the Wild
Rujiao Long, Wen Wang, Nan Xue +4
This paper tackles the problem of table structure parsing (TSP) from images in the wild. In contrast to existing studies that mainly focus on parsing well-aligned tabular images wi…
Learning Local-Global Contextual Adaptation for Multi-Person Pose Estimation
Nan Xue, Tianfu Wu, Gui-Song Xia +1
This paper studies the problem of multi-person pose estimation in a bottom-up fashion. With a new and strong observation that the localization issue of the center-offset formulatio…
PlaneTR: Structure-Guided Transformers for 3D Plane Recovery
Bin Tan, Nan Xue, Song Bai +2
This paper presents a neural network built upon Transformers, namely PlaneTR, to simultaneously detect and reconstruct planes from a single image. Different from previous methods,…
Deep Graph Matching under Quadratic Constraint
Quankai Gao, Fudong Wang, Nan Xue +2
Recently, deep learning based methods have demonstrated promising results on the graph matching problem, by relying on the descriptive capability of deep features extracted on grap…
ReDet: A Rotation-equivariant Detector for Aerial Object Detection
Jiaming Han, Jian Ding, Nan Xue +1
Recently, object detection in aerial images has gained much attention in computer vision. Different from objects in natural images, aerial objects are often distributed with arbitr…
Object Detection in Aerial Images: A Large-Scale Benchmark and Challenges
Jian Ding, Nan Xue, Gui-Song Xia +8
In the past decade, object detection has achieved significant progress in natural images but not in aerial images, due to the massive variations in the scale and orientation of obj…