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PromptPoseFX: Authoring Dynamic Pose-Driven Visual Effects via Language and Multimodal Interaction
The Hong Kong University of Science and Technology
Department of Computer Science and Engineering
MPhil Thesis Defence
Title: "PromptPoseFX: Authoring Dynamic Pose-Driven Visual Effects via Language
and Multimodal Interaction"
By
Miss Kexin ZHENG
Abstract:
Authoring pose-driven visual effects with traditional video editing tools is a
complex and time-consuming task that requires considerable technical expertise
and manual effort. While generative AI models can simplify the workflow,
existing approaches primarily focus on pixel-based video frame generation,
which often alters the original video content and lacks the granularity
required for fine-grained, iterative refinement.
To address these issues, we present PromptPoseFX, an interactive system that
allows creators to author pose-driven visual effects through natural language
and multimodal interaction. Our system leverages Large Language Models (LLMs)
to translate high- level user intent into parameterized procedural graphics
scripts, automatically mapping pose-tracking data to specific effect
parameters. Our script-based approach manages effects as independent layers,
which preserves the original content of the underlying video. To mitigate the
ambiguity of natural language, we design a multimodal interface that supports
(1) direct spatial coordinate selection, (2) temporally grounded prompting,
and (3) dynamically generated parameter controls. We evaluated our system
through a comparison study against a conversational interface baseline and an
exploratory usability study. The results demonstrate that PromptPoseFX offers
significantly higher controllability and precision than conventional
conversational interfaces while maintaining a high level of usability,
effectively lowering the technical barrier to authoring pose-driven visual
effects.
Date: Monday, 2 March 2026
Time: 2:00pm - 4:00pm
Venue: Room 2612A
Lifts 31/32
Chairman: Prof. Pedro SANDER
Committee Members: Prof. Chiew-Lan TAI (Supervisor)
Dr. Xiaojuan MA