T2VTree: User-Centered Visual Analytics for Agent-Assisted Thought-to-Video Authoring

TL;DR

T2VTree is a visual analytics system that facilitates user-centered, multi-scene thought-to-video authoring by representing the process as an editable tree with agent assistance, improving workflow management and reuse.

Contribution

The paper introduces T2VTree, a novel visual analytics approach that visualizes and supports multi-modal, multi-stage thought-to-video creation with agent-assisted planning and editable process trees.

Findings

Supports reliable refinement and editing of video creation workflows.

Enables localized comparison and reuse of authoring steps.

Demonstrated effectiveness through case studies and user evaluation.

Abstract

Generative models have substantially expanded video generation capabilities, yet practical thought-to-video creation remains a multi-stage, multi-modal, and decision-intensive process. However, existing tools either hide intermediate decisions behind repeated reruns or expose operator-level workflows that make exploration traces difficult to manage, compare, and reuse. We present T2VTree, a user-centered visual analytics approach for agent-assisted thought-to-video authoring. T2VTree represents the authoring process as a tree visualization. Each node in the tree binds an editable specification (intent, referenced inputs, workflow choice, prompts, and parameters) with the resulting multimodal outputs, making refinement, branching, and provenance inspection directly operable. To reduce the burden of deciding what to do next, a set of collaborating agents translates step-level intent into an executable plan that remains visible and user-editable before execution. We further implement a visual analytics system that integrates branching authoring with in-place preview and stitching for convergent assembly, enabling end-to-end multi-scene creation without leaving the authoring context. We demonstrate T2VTreeVA through two multi-scene case studies and a comparative user study, showing how the T2VTree visualization and editable agent planning support reliable refinement, localized comparison, and practical reuse in real authoring workflows. T2VTree is available at: https://github.com/tezuka0210/T2VTree.