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Page not found. Your pixels are in another canvas.
A variety of common markup showing how the theme styles them.
Single line blockquote:
Quotes are cool.
Entry | Item | |
---|---|---|
John Doe | 2016 | Description of the item in the list |
Jane Doe | 2019 | Description of the item in the list |
Doe Doe | 2022 | Description of the item in the list |
Header1 | Header2 | Header3 |
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cell1 | cell2 | cell3 |
cell4 | cell5 | cell6 |
cell1 | cell2 | cell3 |
cell4 | cell5 | cell6 |
Foot1 | Foot2 | Foot3 |
Make any link standout more when applying the .btn
class.
Watch out! You can also add notices by appending {: .notice}
to a paragraph.
This is an example of a link.
The abbreviation CSS stands for “Cascading Style Sheets”.
“Code is poetry.” —Automattic
You will learn later on in these tests that word-wrap: break-word;
will be your best friend.
This tag will let you strikeout text.
The emphasize tag should italicize text.
This tag should denote inserted text.
This scarcely known tag emulates keyboard text, which is usually styled like the <code>
tag.
This tag styles large blocks of code.
.post-title { margin: 0 0 5px; font-weight: bold; font-size: 38px; line-height: 1.2; and here's a line of some really, really, really, really long text, just to see how the PRE tag handles it and to find out how it overflows; }
Developers, developers, developers…
–Steve Ballmer
This tag shows bold text.
Getting our science styling on with H2O, which should push the “2” down.
Still sticking with science and Isaac Newton’s E = MC2, which should lift the 2 up.
This allows you to denote variables.
Page not found. Your pixels are in another canvas.
Published in ACM International Conference on Multimedia, 2020
In this work, we present a novel hybrid dynAmic-static Context-aware attenTION NETwork (ACTION-NET) for action assessment in long videos
Recommended citation: Ling-An Zeng, Fa-Ting Hong, Wei-Shi Zheng, Qi-Zhi Yu, Wei Zeng, Yao-Wei Wang, and Jian-Huang Lai. Hybrid Dynamic-static Context-aware Attention Network for Action Assessment in Long Videos. Proc. of ACM International Conference on Multimedia (ACM MM), 2020.
Published in European Conference on Computer Vision, 2020
We address the weakly supervised video highlight detectionproblem for learning to detect the segments that are more attractivein training videos given their video event label but without expensivesupervision of manually annotating highlight segments.
Recommended citation: Fa-Ting Hong, Xuanteng Huang, Wei-Hong Li, and Wei-Shi Zheng. MINI-Net: Multiple Instance Ranking Networkfor Video Highlight Detection. In European Conference on Computer Vision (ECCV), 2020.
Published in International Conference on Computer Vision and Pattern Recognition, 2019
In this work, we propose a deep imPOrtance relatIon NeTwork (POINT) that combines both relation modeling and feature learning.
Recommended citation: Wei-Hong Li, Fa-Ting Hong, and Wei-Shi Zheng. Learning to learn relation for important people detection in still images. In Computer Vision and Pattern Recognition, 2019.
Published in International Conference on Computer Vision and Pattern Recognition, 2020
In this work, we study semi-supervised learning in the context of important people detection and propose a semi-supervised learning method for this task.
Recommended citation: Fa-Ting Hong, Wei-Hong Li and Wei-Shi Zheng. Learning to Detect Important People in Unlabelled Images for Semi-supervised Important People Detection. In Computer Vision and Pattern Recognition, 2020.
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Published in 2017 IEEE International Conference on Real-time Computing and Robotics, 2017
The paper introduces a method which is based o n genetic algorithm to select more properly parameters for local path planning of mobile robot.
Recommended citation: Liang, Y., Hong, F., Lin, Q., Bi, S., & Feng, L. (2017, July). Optimization of robot path planning parameters based on genetic algorithm. In 2017 IEEE International Conference on Real-time Computing and Robotics (RCAR) (pp. 529-534). IEEE.