AnimationDiff: A Visual Comparison Tool for Generated 3D Character Animations

2026-05-01

AI Summary

While generative methods enable efficient creation of diverse 3D character animations, their practical utility is hindered by temporal misalignment and the overwhelming scale of generated data, which complicates effective comparison and selection. To address this challenge, this work proposes AnimationDiff—a visualization tool specifically designed for comparative analysis of generative 3D animations. AnimationDiff integrates contextual scene rendering with switchable overlay and side-by-side views to embed spatial information, and introduces a novel Temporal Lenses technique to provide an overview of full-time sequences while enabling precise temporal alignment. Complemented by a spatiotemporal filtering mechanism to mitigate information overload, the system significantly enhances comparison efficiency and user experience, as demonstrated in user studies. AnimationDiff thus establishes an effective design paradigm for the visual comparison of motion data.

Abstract

Creating 3D character animations traditionally requires significant time and effort from the animator. Advancements in generative methods now enable easy creation of multiple character animation variations for use or further editing. However, this capability introduces a new challenge in comparing character animations to select the best animation, which is challenging due to temporal misalignment and the large amount of spatial data. We present AnimationDiff, a visual comparison tool for generated character animations. AnimationDiff enables contextual comparisons in the intended scene and camera angle, and embedding of spatial information by combining established animation visualization techniques and easy switching between overlaid and side-by-side comparisons. AnimationDiff also supports filtering to handle information overload, and Temporal Lenses that visualize entire animations over time for overview, alignment, and comparison. We evaluated AnimationDiff in a user study, showcasing its efficacy in animation comparison and providing design insights for comparing motion.

Problem

• 3D character animation
• animation comparison
• temporal misalignment
• spatial data
• motion visualization

Innovation

• AnimationDiff
• visual comparison
• 3D character animation
• Temporal Lenses
• motion visualization