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Kuizong Wu

dblp:402/3262 · DBLP profile ↗
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1ranked-venue papers
1as first author
1since 2021 · last 2025
—ORCID · none

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

Artificial intelligence and machine learning · 1 · 1 first-author · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author · 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
Visual content generation and editing · 100%

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

TopicWeightPapersLastEvidence papers
Visual content generation and editing
video generation
0.912025
AutoMV: An Autonomous Agent Framework for Real Estate Marketing Video Generation · AAAI 2025
Visual content generation and editing
multimedia content creation
0.312025
AutoMV: An Autonomous Agent Framework for Real Estate Marketing Video Generation · AAAI 2025

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

video synthesis · 0.9tool selection · 0.9large language model agent · 0.9
YearPublicationVenuePosition
2025 AutoMV: An Autonomous Agent Framework for Real Estate Marketing Video Generation
abstract
In this paper, we introduce AutoMV, an autonomous agent framework designed for generating real estate marketing videos. The framework integrates a diverse set of existing models into a tool library, allowing the agent to intelligently select and execute the appropriate tools. Given property images and text, the agent decomposes the task into manageable subtasks, generating storyline directives and corresponding camera movement trajectories to guide the video production process. By automatically applying video synthesis techniques and incorporating multimedia elements such as subtitles and background music, the agent transforms static real estate images into dynamic, visually appealing videos, thereby optimizing their impact for digital marketing purposes.
Kuizong Wu, Shaozu Yuan, Chang Shen, Meng Chen 0006
AAAI1