5 citations · 7 across the 7 of their papers we have counts for
8 papers
Temporal Point Cloud Completion with Pose Disturbance
Jieqi Shi, Lingyun Xu, Peiliang Li +2
Point clouds collected by real-world sensors are always unaligned and sparse, which makes it hard to reconstruct the complete shape of object from a single frame of data. In this w…
PSE-Match: A Viewpoint-free Place Recognition Method with Parallel Semantic Embedding
Peng Yin, Lingyun Xu, Ziyue Feng +2
Accurate localization on autonomous driving cars is essential for autonomy and driving safety, especially for complex urban streets and search-and-rescue subterranean environments…
3D Segmentation Learning from Sparse Annotations and Hierarchical Descriptors
Peng Yin, Lingyun Xu, Jianmin Ji +2
One of the main obstacles to 3D semantic segmentation is the significant amount of endeavor required to generate expensive point-wise annotations for fully supervised training. To…
i3dLoc: Image-to-range Cross-domain Localization Robust to Inconsistent Environmental Conditions
Peng Yin, Lingyun Xu, Ji Zhang +2
We present a method for localizing a single camera with respect to a point cloud map in indoor and outdoor scenes. The problem is challenging because correspondences of local invar…
MRS-VPR: a multi-resolution sampling based global visual place recognition method
Peng Yin, Rangaprasad Arun Srivatsan, Yin Chen +7
Place recognition and loop closure detection are challenging for long-term visual navigation tasks. SeqSLAM is considered to be one of the most successful approaches to achieving l…
A Multi-Domain Feature Learning Method for Visual Place Recognition
Peng Yin, Lingyun Xu, Xueqian Li +6
Visual Place Recognition (VPR) is an important component in both computer vision and robotics applications, thanks to its ability to determine whether a place has been visited and…