Papers 3D Geometry Perception
“3D Geometry Perception” 태그가 달린 논문 5편 · 필터 해제
ConDor: Self-Supervised Canonicalization of 3D Pose for Partial Shapes
Progress in 3D object understanding has relied on manually canonicalized shape datasets that contain instances with consistent position and orientation (3D pose). This has made it hard to generalize these methods to in-t…
3D Canonicalization3D Geometry Perception3D Part Segmentation3D Pose Estimation+1Self-supervised Learning of Occlusion Aware Flow Guided 3D Geometry Perception with Adaptive Cross Weighted Loss from Monocular Videos
Self-supervised deep learning-based 3D scene understanding methods can overcome the difficulty of acquiring the densely labeled ground-truth and have made a lot of advances. However, occlusions and moving objects are sti…
3D geometry3D Geometry PerceptionCamera Pose EstimationOptical Flow Estimation+3ACSC: Automatic Calibration for Non-repetitive Scanning Solid-State LiDAR and Camera Systems
Recently, the rapid development of Solid-State LiDAR (SSL) enables low-cost and efficient obtainment of 3D point clouds from the environment, which has inspired a large quantity of studies and applications. However, the …
3D Geometry PerceptionCamera Auto-Calibration3D Point Capsule Networks
In this paper, we propose 3D point-capsule networks, an auto-encoder designed to process sparse 3D point clouds while preserving spatial arrangements of the input data. 3D capsule networks arise as a direct consequence o…
3D Feature Matching3D Geometry Perception3D Object Classification3D Object Reconstruction+6SIGNet: Semantic Instance Aided Unsupervised 3D Geometry Perception
Unsupervised learning for geometric perception (depth, optical flow, etc.) is of great interest to autonomous systems. Recent works on unsupervised learning have made considerable progress on perceiving geometry; however…
3D geometry3D Geometry PerceptionDepth EstimationDepth Prediction+3