12 citations · 35 across the 26 of their papers we have counts for
14 papers · 1 filter
Convex Hull-based Algebraic Constraint for Visual Quadric SLAM
Xiaolong Yu, Junqiao Zhao, Shuangfu Song +4
Using Quadrics as the object representation has the benefits of both generality and closed-form projection derivation between image and world spaces. Although numerous constraints…
MutualVPR: A Mutual Learning Framework for Resolving Supervision Inconsistencies via Adaptive Clustering
Qiwen Gu, Xufei Wang, Junqiao Zhao +4
Visual Place Recognition (VPR) enables robust localization through image retrieval based on learned descriptors. However, drastic appearance variations of images at the same place…
VNI-Net: Vector Neurons-based Rotation-Invariant Descriptor for LiDAR Place Recognition
Gengxuan Tian, Junqiao Zhao, Yingfeng Cai +3
LiDAR-based place recognition plays a crucial role in Simultaneous Localization and Mapping (SLAM) and LiDAR localization. Despite the emergence of various deep learning-based and…
Learning Sequence Descriptor based on Spatio-Temporal Attention for Visual Place Recognition
Junqiao Zhao, Fenglin Zhang, Yingfeng Cai +4
Visual Place Recognition (VPR) aims to retrieve frames from a geotagged database that are located at the same place as the query frame. To improve the robustness of VPR in perceptu…
Patch-NetVLAD+: Learned patch descriptor and weighted matching strategy for place recognition
Yingfeng Cai, Junqiao Zhao, Jiafeng Cui +3
Visual Place Recognition (VPR) in areas with similar scenes such as urban or indoor scenarios is a major challenge. Existing VPR methods using global descriptors have difficulty ca…
DSC: Deep Scan Context Descriptor for Large-Scale Place Recognition
Jiafeng Cui, Tengfei Huang, Yingfeng Cai +3
LiDAR-based place recognition is an essential and challenging task both in loop closure detection and global relocalization. We propose Deep Scan Context (DSC), a general and discr…
Unsupervised Joint Learning of Depth, Optical Flow, Ego-motion from Video
Jianfeng Li, Junqiao Zhao, Shuangfu Song +1
Estimating geometric elements such as depth, camera motion, and optical flow from images is an important part of the robot's visual perception. We use a joint self-supervised metho…
Dense Dual-Path Network for Real-time Semantic Segmentation
Xinneng Yang, Yan Wu, Junqiao Zhao +1
Semantic segmentation has achieved remarkable results with high computational cost and a large number of parameters. However, real-world applications require efficient inference sp…
Occlusion Aware Unsupervised Learning of Optical Flow From Video
Jianfeng Li, Junqiao Zhao, Tiantian Feng +2
In this paper, we proposed an unsupervised learning method for estimating the optical flow between video frames, especially to solve the occlusion problem. Occlusion is caused by t…
Detecting Lane and Road Markings at A Distance with Perspective Transformer Layers
Zhuoping Yu, Xiaozhou Ren, Yuyao Huang +2
Accurate detection of lane and road markings is a task of great importance for intelligent vehicles. In existing approaches, the detection accuracy often degrades with the increasi…
Vision-based Semantic Mapping and Localization for Autonomous Indoor Parking
Yewei Huang, Junqiao Zhao, Xudong He +2
In this paper, we proposed a novel and practical solution for the real-time indoor localization of autonomous driving in parking lots. High-level landmarks, the parking slots, are…
DLO: Direct LiDAR Odometry for 2.5D Outdoor Environment
Lu Sun, Junqiao Zhao, Xudong He +1
For autonomous vehicles, high-precision real-time localization is the guarantee of stable driving. Compared with the visual odometry (VO), the LiDAR odometry (LO) has the advantage…
VH-HFCN based Parking Slot and Lane Markings Segmentation on Panoramic Surround View
Yan Wu, Tao Yang, Junqiao Zhao +2
The automatic parking is being massively developed by car manufacturers and providers. Until now, there are two problems with the automatic parking. First, there is no openly-avail…
Semantic Segmentation via Highly Fused Convolutional Network with Multiple Soft Cost Functions
Tao Yang, Yan Wu, Junqiao Zhao +1
Semantic image segmentation is one of the most challenged tasks in computer vision. In this paper, we propose a highly fused convolutional network, which consists of three parts: f…