activity
20182022
most citedUnsupervised Joint Learning of Depth, Optical Flow, Ego-motion from Video

4 citations · 7 across the 5 of their papers we have counts for

collaborators

13 papers

cs.RO20222 cited

DL-SLOT: Dynamic Lidar SLAM and Object Tracking Based On Graph Optimization

Xuebo Tian, Junqiao Zhao, Chen Ye

Ego-pose estimation and dynamic object tracking are two key issues in an autonomous driving system. Two assumptions are often made for them, i.e. the static world assumption of sim…

cs.CV2022

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…

cs.CV20214 cited

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…

cs.CV2020

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…

cs.CV2020

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…

cs.CV2020

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…