Xiaohan Nie

Orcid: 0000-0002-2814-0369

According to our database1, Xiaohan Nie authored at least 15 papers between 2011 and 2023.

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Bibliography

2023
Movies2Scenes: Using Movie Metadata to Learn Scene Representation.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022
Movies2Scenes: Learning Scene Representations Using Movie Similarities.
CoRR, 2022

Depth-Guided Sparse Structure-from-Motion for Movies and TV Shows.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021
A Robust and Efficient Framework for Sports-Field Registration.
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2021

Shot Contrastive Self-Supervised Learning for Scene Boundary Detection.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020
Computer-Aided Diagnosis and Staging of Pancreatic Cancer Based on CT Images.
IEEE Access, 2020

2018
Attribute And-Or Grammar for Joint Parsing of Human Pose, Parts and Attributes.
IEEE Trans. Pattern Anal. Mach. Intell., 2018

2017
Spatial-Temporal Hierarchical Model for Joint Learning and Inference of Human Action and Pose.
PhD thesis, 2017

Monocular 3D Human Pose Estimation by Predicting Depth on Joints.
Proceedings of the IEEE International Conference on Computer Vision, 2017

2016
Attribute And-Or Grammar for Joint Parsing of Human Attributes, Part and Pose.
CoRR, 2016

2015
Joint action recognition and pose estimation from video.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015

2014
Animated Pose Templates for Modeling and Detecting Human Actions.
IEEE Trans. Pattern Anal. Mach. Intell., 2014

Mining discriminative 3D Poselet for cross-view action recognition.
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2014

Cross-View Action Modeling, Learning, and Recognition.
Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014

2011
Experts-Shift: Learning active spatial classification experts for keyframe-based video segmentation.
Proceedings of the IEEE Workshop on Applications of Computer Vision (WACV 2011), 2011


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