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V2M4: 4D Mesh Animation Reconstruction from a Single Monocular Video

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arxiv 2503.09631 v2 pith:ZW6Q72WI submitted 2025-03-11 cs.GR eess.IV

classification cs.GReess.IV
keywords meshmethodanimationgenerationmodelstexturev2m4video
verification ladder T0 review T1 audit T2 compute T3 formal
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We present V2M4, a novel 4D reconstruction method that directly generates a usable 4D mesh animation asset from a single monocular video. Unlike existing approaches that rely on priors from multi-view image and video generation models, our method is based on native 3D mesh generation models. Naively applying 3D mesh generation models to generate a mesh for each frame in a 4D task can lead to issues such as incorrect mesh poses, misalignment of mesh appearance, and inconsistencies in mesh geometry and texture maps. To address these problems, we propose a structured workflow that includes camera search and mesh reposing, condition embedding optimization for mesh appearance refinement, pairwise mesh registration for topology consistency, and global texture map optimization for texture consistency. Our method outputs high-quality 4D animated assets that are compatible with mainstream graphics and game software. Experimental results across a variety of animation types and motion amplitudes demonstrate the generalization and effectiveness of our method. Project page: https://windvchen.github.io/V2M4/.

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Cited by 4 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. HAT-4D: Lifting Monocular Video for 4D Multi-Object Interactions via Human-Agent Collaboration

    cs.CV 2026-06 unverdicted novelty 6.0 of 10

    HAT-4D presents an agentic VLM-plus-human-in-the-loop pipeline for monocular 4D multi-object interaction reconstruction and releases the MVOIK-4D benchmark.

  2. Follow Your Track: Precise Skeleton Animation Controlled by 3D Trajectories

    cs.CV 2026-06 unverdicted novelty 6.0 of 10

    ACT is a trajectory-conditioned framework for topology-general skeletal animation that injects 3D point trajectories from monocular video into skeletons via a Routed Trajectory Injector for improved fidelity and tempo...

  3. Sculpt4D: Generating 4D Shapes via Sparse-Attention Diffusion Transformers

    cs.CV 2026-04 unverdicted novelty 6.0 of 10

    Sculpt4D generates temporally coherent 4D shapes by integrating a block sparse attention mechanism with time-decaying mask into a pretrained 3D diffusion transformer, achieving SOTA results with 56% less computation.

  4. Advances in 4D Representation: Geometry, Motion, and Interaction

    cs.CV 2025-10 conditional novelty 4.0 of 10

    A representation-centric survey of 4D generation and reconstruction, organized by geometry, motion, and interaction, with qualitative trade-off comparisons across seven representation families.

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