Strike a Chord! Modal Kinetic Typography
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Abstract (arXiv)
We introduce modal kinetic typography, which animates a vector glyph to express a semantic concept while keeping it legible. Our key idea is to build motion from the glyph's natural vibration modes. Specifically, a finite-element eigenproblem assembled from the vector outline yields the glyph's softest modes, for the whole letter and for each of its parts, allowing it to bend. The problem's zero-energy solutions, i.e., rigid translations and rotations, are applied in closed form to each part, allowing parts to also move as blocks. To animate the glyph, a frozen video diffusion model supervises only the modes' amplitudes and phases. Our modal approach addresses two weaknesses of prior work. Free-form point optimization under video score distillation (SDS) moves each point and frame independently along noisy gradients, tearing the outline and causing jitter. In contrast, our modes are smooth along the outline and driven by a few whole-cycle harmonics, which restricts these gradients to smooth, seamlessly looping motion. On the other hand, structured alternatives rely on skeletons or keypoints from category-specific priors, whereas our modes come from the glyph itself; the only prior is a list naming each letter's moving parts, generated once for the whole alphabet by a language model. In modal kinetic typography, shape and motion are disentangled by construction: a single base outline is sculpted toward the concept, and the modal drive cannot alter it, so a letter can also be animated without being reshaped. Our method produces more articulated and smoother motion than Dynamic Typography and AniClipart at comparable or better concept alignment, with less glyph tearing than Dynamic Typography, and is preferred by human raters, including in a frozen-shape setting where motion alone must carry the concept. Our results were also preferred over Astra (GPT-6) by human raters.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 19 of its 33 references that are in the map. First posted on arXiv 29 Sep 2026.
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19 of 33 references.
References · 19
- 2022DreamFusion: Text-to-3D using 2D Diffusioncited by 3,025
- 2023ModelScope Text-to-Video Technical Reportcited by 658
- 2023Generative Image Dynamicscited by 94
- 2023Word-As-Image for Semantic Typographycited by 63
- 2023Breathing Life Into Sketches Using Text-to-Video Priorscited by 48
- 2023DS-Fusion: Artistic Typography via Discriminated and Stylized Diffusioncited by 26
- 2023As-Plausible-As-Possible: Plausibility-Aware Mesh Deformation Using 2D Diffusion Priorscited by 25
- 2024AniClipart: Clipart Animation with Text-to-Video Priorscited by 17
- 2025Articulated Kinematics Distillation from Video Diffusion Modelscited by 13
- 2017Localized Manifold Harmonics for Spectral Shape Analysiscited by 12
- 2024Dynamic Typography: Bringing Text to Life via Video Diffusion Priorcited by 12
- 2024Kinetic Typography Diffusion Modelcited by 9
7 more
- 2024MetaDesigner: Advancing Artistic Typography Through AI-Driven, User-Centric, and Multilingual WordArt Synthesiscited by 6
- 2025Animus3D: Text-driven 3D Animation via Motion Score Distillationcited by 5
- 2024VitaGlyph: Vitalizing Artistic Typography with Flexible Dual-branch Diffusion Modelscited by 4
- 2026LiveSVG: Zero-Shot SVG Animation via Video Generationcited by 2
- 2024Actuators `A La Mode: Modal Actuations for Soft Body Locomotioncited by 1
- 2025Differentiable Variable Fontscited by 1
- 2026Sketch2Motion: Text-driven 2D Sketch to 3D Animation via Diffusion-guided Skeleton Optimizationcited by 1
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- 2026VecGlypher: Unified Vector Glyph Generation with Language Models
- 2025SMooGPT: Stylized Motion Generation using Large Language Models
- 2024MMoFusion: Multi-modal Co-Speech Motion Generation with Diffusion Model
- 2025StyleMotif: Multi-Modal Motion Stylization using Style-Content Cross Fusion
- 2026OmniLottie: Generating Vector Animations via Parameterized Lottie Tokens
- 2025From Rigging to Waving: 3D-Guided Diffusion for Natural Animation of Hand-Drawn Characters
- 2025OmniMotion-X: Versatile Multimodal Whole-Body Motion Generation
- 2022FLAME: Free-form Language-based Motion Synthesis & Editing