Shida Guo

dblp:359/4397 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2023
0009-0000-5277-0873ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer graphics and multimedia
1 paper
Multimedia systems and quality of experience · 50% Multimedia analysis and retrieval · 50%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Multimedia analysis and retrieval
object tracking
0.712023
H2V4Sports: Real-Time Horizontal-to-Vertical Video Converter for Sports Lives via Fast Object Detection and Tracking · ACM Multimedia 2023
Multimedia systems and quality of experience › content adaptation
video adaptation
0.712023
H2V4Sports: Real-Time Horizontal-to-Vertical Video Converter for Sports Lives via Fast Object Detection and Tracking · ACM Multimedia 2023

Methods — techniques the papers use, named apart from their topics

pruning · 0.7object tracking · 0.7object detection · 0.7
YearPublicationVenuePosition
2023 H2V4Sports: Real-Time Horizontal-to-Vertical Video Converter for Sports Lives via Fast Object Detection and Tracking
abstract
We present H2V4Sports, a real-time horizontal-to-vertical video converter specifically designed for sports live broadcasts. With the increasing demand of smartphone users who prefer to watch sports events on their vertical screens anywhere, anytime, our platform provides a seamless viewing experience. We achieve this by fine-tuning and pruning an object detector and tracker, which enables us to provide real-time, accurate key-object tracking results despite the complexity of sports scenes. Additionally, we propose a video virtual director platform that captures the most informative vertical zones from horizontal video live frames using various director logic for a smooth frame-to-frame transition. We have successfully demonstrated our platform in two popular sports: basketball and diving, and the results indicate that our technology delivers high-quality vertical scenes that are beneficial for smartphone users and other vertical scenarios.
Kaidong Li, Zihan Song 0003, Shida Guo, Xin Wang 0019, Xuguang Duan, Wenwu Zhu 0001
ACM Multimedia6