Chengyu Qiao

Orcid: 0000-0003-2413-6837

According to our database1, Chengyu Qiao authored at least 15 papers between 2019 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2023
PT-FlowNet: Scene Flow Estimation on Point Clouds With Point Transformer.
IEEE Robotics Autom. Lett., May, 2023

TransAPR: Absolute Camera Pose Regression With Spatial and Temporal Attention.
IEEE Robotics Autom. Lett., 2023

Objects matter: Learning object relation graph for robust absolute pose regression.
Neurocomputing, 2023

Rethinking Cross-Entropy Loss for Stereo Matching Networks.
CoRR, 2023

iVS-Net: Learning Human View Synthesis from Internet Videos.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022
Objects Matter: Learning Object Relation Graph for Robust Camera Relocalization.
CoRR, 2022

2021
PGNet: Panoptic parsing guided deep stereo matching.
Neurocomputing, 2021

Superline: A Robust Line Segment Feature for Visual SLAM.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2021

Real-time Instance Segmentation with Discriminative Orientation Maps.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

2020
Simultaneous Semantic Segmentation and Depth Completion with Constraint of Boundary.
Sensors, 2020

SGNet: Semantics Guided Deep Stereo Matching.
Proceedings of the Computer Vision - ACCV 2020 - 15th Asian Conference on Computer Vision, Kyoto, Japan, November 30, 2020

2019
Boundary-Aware CNN for Semantic Segmentation.
IEEE Access, 2019

Self-supervised Homography Prediction CNN for Accurate Lane Marking Fitting.
Proceedings of the Pattern Recognition and Computer Vision - Second Chinese Conference, 2019

3D Reconstruction by Single Camera Omnidirectional Multi-Stereo System.
Proceedings of the 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2019

Accurate and Real-Time Object Detection Based on Bird's Eye View on 3D Point Clouds.
Proceedings of the 2019 International Conference on 3D Vision, 2019


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