Yu Cheng

Orcid: 0000-0002-9830-0081

Affiliations:

National University of Singapore, Yale-NUS College

According to our database¹, Yu Cheng authored at least 22 papers between 2017 and 2023.

Collaborative distances:

Dijkstra number² of five.
Erdős number³ of four.

Timeline

Legend:

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Article

PhD thesis

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Other

Bibliography

2023

Bottom-up 2D pose estimation via dual anatomical centers for small-scale persons.

[BibT_eX]

[DOI]

Pattern Recognit., July, 2023

Dual Networks Based 3D Multi-Person Pose Estimation From Monocular Video.

[BibT_eX]

[DOI]

Yu Cheng

Bo Wang

Robby T. Tan

IEEE Trans. Pattern Anal. Mach. Intell., 2023

ORTexME: Occlusion-Robust Human Shape and Pose via Temporal Average Texture and Mesh Encoding.

[BibT_eX]

[DOI]

Yu Cheng

Bo Wang

Robby T. Tan

CoRR, 2023

Unified Single-Stage Transformer Network for Efficient RGB-T Tracking.

[BibT_eX]

[DOI]

CoRR, 2023

DecenterNet: Bottom-Up Human Pose Estimation Via Decentralized Pose Representation.

[BibT_eX]

[DOI]

Proceedings of the 31st ACM International Conference on Multimedia, 2023

DSFNet: Dual Space Fusion Network for Occlusion-Robust 3D Dense Face Alignment.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2021

Monocular 3D Multi-Person Pose Estimation by Integrating Top-Down and Bottom-Up Networks.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Graph and Temporal Convolutional Networks for 3D Multi-person Pose Estimation in Monocular Videos.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

DSAM: A Distance Shrinking with Angular Marginalizing Loss for High Performance Vehicle Re-identificatio.

[BibT_eX]

[DOI]

CoRR, 2020

Object Tracking Using Spatio-Temporal Future Prediction.

[BibT_eX]

[DOI]

CoRR, 2020

Object Tracking Using Spatio-Temporal Networks for Future Prediction Location.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2020, 2020

3D Human Pose Estimation Using Spatio-Temporal Networks with Explicit Occlusion Training.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Occlusion-Aware Networks for 3D Human Pose Estimation in Video.

[BibT_eX]

[DOI]

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Look across Elapse: Disentangled Representation Learning and Photorealistic Cross-Age Face Synthesis for Age-Invariant Face Recognition.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Look Across Elapse: Disentangled Representation Learning and Photorealistic Cross-Age Face Synthesis for Age-Invariant Face Recognition.

[BibT_eX]

[DOI]

CoRR, 2018

Understanding Humans in Crowded Scenes: Deep Nested Adversarial Learning and A New Benchmark for Multi-Human Parsing.

[BibT_eX]

[DOI]

CoRR, 2018

Understanding Humans in Crowded Scenes: Deep Nested Adversarial Learning and A New Benchmark for Multi-Human Parsing.

[BibT_eX]

[DOI]

Proceedings of the 2018 ACM Multimedia Conference on Multimedia Conference, 2018

3D-Aided Deep Pose-Invariant Face Recognition.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Towards Pose Invariant Face Recognition in the Wild.

[BibT_eX]

[DOI]

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

Dual-Mode Vehicle Motion Pattern Learning for High Performance Road Traffic Anomaly Detection.

[BibT_eX]

[DOI]

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2018

2017

High Performance Large Scale Face Recognition with Multi-cognition Softmax and Feature Retrieval.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE International Conference on Computer Vision Workshops, 2017

Know You at One Glance: A Compact Vector Representation for Low-Shot Learning.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE International Conference on Computer Vision Workshops, 2017

Yu Cheng

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