Search Results for author:
Found 21 papers, 10 papers with code
First Mapping the Canopy Height of Primeval Forests in the Tallest Tree Area of Asia
We proposed a method to map the canopy height of the primeval forest within the world-level giant tree distribution area by using a spaceborne LiDAR fusion satellite imagery (Global Ecosystem Dynamics Investigation (GEDI), ICESat-2, and Sentinel-2) driven deep learning modeling.
On the Estimation of Image-matching Uncertainty in Visual Place Recognition
In Visual Place Recognition (VPR) the pose of a query image is estimated by comparing the image to a map of reference images with known reference poses.
PointeNet: A Lightweight Framework for Effective and Efficient Point Cloud Analysis
The DSE module, designed for real-world autonomous driving scenarios, enhances the semantic perception of point clouds, particularly for distant points.
Cross-BERT for Point Cloud Pretraining
By performing cross-modal interaction, Cross-BERT can smoothly reconstruct the masked tokens during pretraining, leading to notable performance enhancements for downstream tasks.
MuVieCAST: Multi-View Consistent Artistic Style Transfer
We introduce MuVieCAST, a modular multi-view consistent style transfer network architecture that enables consistent style transfer between multiple viewpoints of the same scene.
UniBEV: Multi-modal 3D Object Detection with Uniform BEV Encoders for Robustness against Missing Sensor Modalities
To validate its effectiveness, we compare UniBEV to state-of-the-art BEVFusion and MetaBEV on nuScenes over all sensor input combinations.
PolyGNN: Polyhedron-based Graph Neural Network for 3D Building Reconstruction from Point Clouds
We present PolyGNN, a polyhedron-based graph neural network for 3D building reconstruction from point clouds.
CoPR: Towards Accurate Visual Localization With Continuous Place-descriptor Regression
Firstly, the reference images for VPR are only available at sparse poses in a map, which enforces an upper bound on the maximum achievable localization accuracy through VPR.
Push-the-Boundary: Boundary-aware Feature Propagation for Semantic Segmentation of 3D Point Clouds
To improve the segmentation near object boundaries, we propose a boundary-aware feature propagation mechanism.
3DLG-Detector: 3D Object Detection via Simultaneous Local-Global Feature Learning
Capturing both local and global features of irregular point clouds is essential to 3D object detection (3OD).
CSDN: Cross-modal Shape-transfer Dual-refinement Network for Point Cloud Completion
The first module transfers the intrinsic shape characteristics from single images to guide the geometry generation of the missing regions of point clouds, in which we propose IPAdaIN to embed the global features of both the image and the partial point cloud into completion.
Ranked #2 on
Point Cloud Completion
on ShapeNet-ViPC
DDL-MVS: Depth Discontinuity Learning for MVS Networks
We validate our idea and demonstrate that our strategies can be easily integrated into the existing learning-based MVS pipeline where the reconstruction depends on high-quality depth map estimation.
PSSNet: Planarity-sensible Semantic Segmentation of Large-scale Urban Meshes
The over-segmentation step generates an initial set of mesh segments that capture the planar and non-planar regions of urban scenes.
HRBF-Fusion: Accurate 3D reconstruction from RGB-D data using on-the-fly implicits
However, due to the discrete nature and limited resolution of their surface representations (e. g., point- or voxel-based), existing approaches suffer from the accumulation of errors in camera tracking and distortion in the reconstruction, which leads to an unsatisfactory 3D reconstruction.
City3D: Large-Scale Building Reconstruction from Airborne LiDAR Point Clouds
A major challenge of urban reconstruction from airborne LiDAR point clouds lies in that the vertical walls are typically missing.
Reconstructing Compact Building Models from Point Clouds Using Deep Implicit Fields
While three-dimensional (3D) building models play an increasingly pivotal role in many real-world applications, obtaining a compact representation of buildings remains an open problem.
GlobalMatch: Registration of Forest Terrestrial Point Clouds by Global Matching of Relative Stem Positions
Registering point clouds of forest environments is an essential prerequisite for LiDAR applications in precision forestry.
3D Instance Segmentation of MVS Buildings
Based on these global masks, 3D roof instances are segmented out by mask back-projections and extended to the entire building instances through a Markov random field optimization.
SUM: A Benchmark Dataset of Semantic Urban Meshes
The contributions of this work are threefold: (1) a new benchmark dataset of semantic urban meshes, (2) a novel semi-automatic annotation framework, and (3) an annotation tool for 3D meshes.
An End-to-End Geometric Deficiency Elimination Algorithm for 3D Meshes
The 3D mesh is an important representation of geometric data.
PolyFit: Polygonal Surface Reconstruction From Point Clouds
We show that reconstruction from point clouds can be cast as a binary labeling problem.
