Zhizhong Li

Orcid: 0000-0003-0574-2487

Affiliations:
  • SenseTime, Hong Kong
  • Chinese University of Hong Kong, Hong Kong (PhD 2019)


According to our database1, Zhizhong Li authored at least 14 papers between 2015 and 2023.

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

Timeline

Legend:

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PhD thesis 
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Links

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Bibliography

2023
A Coarse-to-Fine Framework for Automatic Video Unscreen.
IEEE Trans. Multim., 2023

Get the Best of Both Worlds: Improving Accuracy and Transferability by Grassmann Class Representation.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022
Collaborative Anomaly Detection.
CoRR, 2022

ViM: Out-Of-Distribution with Virtual-logit Matching.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021
MMOCR: A Comprehensive Toolbox for Text Detection, Recognition and Understanding.
Proceedings of the MM '21: ACM Multimedia Conference, Virtual Event, China, October 20, 2021

2020
Parallel Multi-Environment Shaping Algorithm for Complex Multi-step Task.
Neurocomputing, 2020

Regularizing Reasons for Outfit Evaluation with Gradient Penalty.
CoRR, 2020

2019
Biased Estimates of Advantages over Path Ensembles.
CoRR, 2019

Policy Continuation with Hindsight Inverse Dynamics.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Convolutional Sequence Generation for Skeleton-Based Action Synthesis.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

2017
Integrating Specialized Classifiers Based on Continuous Time Markov Chain.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

PolyNet: A Pursuit of Structural Diversity in Very Deep Networks.
Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

2015
Determining step sizes in geometric optimization algorithms.
Proceedings of the IEEE International Symposium on Information Theory, 2015

A new retraction for accelerating the Riemannian three-factor low-rank matrix completion algorithm.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015


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