8 citations · 24 across the 9 of their papers we have counts for
10 papers
Geo-ConvGRU: Geographically Masked Convolutional Gated Recurrent Unit for Bird-Eye View Segmentation
Guanglei Yang, Yongqiang Zhang, Wanlong Li +5
Convolutional Neural Networks (CNNs) have significantly impacted various computer vision tasks, however, they inherently struggle to model long-range dependencies explicitly due to…
Self-supervised Event-based Monocular Depth Estimation using Cross-modal Consistency
Junyu Zhu, Lina Liu, Bofeng Jiang +4
An event camera is a novel vision sensor that can capture per-pixel brightness changes and output a stream of asynchronous ``events''. It has advantages over conventional cameras i…
Semi-Supervised Learning for Visual Bird's Eye View Semantic Segmentation
Junyu Zhu, Lina Liu, Yu Tang +3
Visual bird's eye view (BEV) semantic segmentation helps autonomous vehicles understand the surrounding environment only from images, including static elements (e.g., roads) and dy…
HybridPoint: Point Cloud Registration Based on Hybrid Point Sampling and Matching
Yiheng Li, Canhui Tang, Runzhao Yao +3
Patch-to-point matching has become a robust way of point cloud registration. However, previous patch-matching methods employ superpoints with poor localization precision as nodes,…
Graph-based Topology Reasoning for Driving Scenes
Tianyu Li, Li Chen, Huijie Wang +10
Understanding the road genome is essential to realize autonomous driving. This highly intelligent problem contains two aspects - the connection relationship of lanes, and the assig…
FG-Depth: Flow-Guided Unsupervised Monocular Depth Estimation
Junyu Zhu, Lina Liu, Yong Liu +3
The great potential of unsupervised monocular depth estimation has been demonstrated by many works due to low annotation cost and impressive accuracy comparable to supervised metho…
Semantic Segmentation-assisted Scene Completion for LiDAR Point Clouds
Xuemeng Yang, Hao Zou, Xin Kong +5
Outdoor scene completion is a challenging issue in 3D scene understanding, which plays an important role in intelligent robotics and autonomous driving. Due to the sparsity of LiDA…
SA-LOAM: Semantic-aided LiDAR SLAM with Loop Closure
Lin Li, Xin Kong, Xiangrui Zhao +4
LiDAR-based SLAM system is admittedly more accurate and stable than others, while its loop closure detection is still an open issue. With the development of 3D semantic segmentatio…
F-Siamese Tracker: A Frustum-based Double Siamese Network for 3D Single Object Tracking
Hao Zou, Jinhao Cui, Xin Kong +4
This paper presents F-Siamese Tracker, a novel approach for single object tracking prominently characterized by more robustly integrating 2D and 3D information to reduce redundant…
Semantic Graph Based Place Recognition for 3D Point Clouds
Xin Kong, Xuemeng Yang, Guangyao Zhai +6
Due to the difficulty in generating the effective descriptors which are robust to occlusion and viewpoint changes, place recognition for 3D point cloud remains an open issue. Unlik…