LIM: Large Interpolator Model for Dynamic Reconstruction

• URL: http://arxiv.org/abs/2503.22537v1
• Date: Fri, 28 Mar 2025 15:36:53 GMT
• Title: LIM: Large Interpolator Model for Dynamic Reconstruction
• Abstract summary: Existing 4D reconstruction approaches are limited by category-specific models or slow optimization-based methods.<n>We present the Large Interpolation Model (LIM), a transformer-based feed-forward solution for interpolating implicit 3D representations across time.
• Score: 26.65191922949358
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Reconstructing dynamic assets from video data is central to many in computer vision and graphics tasks. Existing 4D reconstruction approaches are limited by category-specific models or slow optimization-based methods. Inspired by the recent Large Reconstruction Model (LRM), we present the Large Interpolation Model (LIM), a transformer-based feed-forward solution, guided by a novel causal consistency loss, for interpolating implicit 3D representations across time. Given implicit 3D representations at times $t_0$ and $t_1$, LIM produces a deformed shape at any continuous time $t\in[t_0,t_1]$, delivering high-quality interpolated frames in seconds. Furthermore, LIM allows explicit mesh tracking across time, producing a consistently uv-textured mesh sequence ready for integration into existing production pipelines. We also use LIM, in conjunction with a diffusion-based multiview generator, to produce dynamic 4D reconstructions from monocular videos. We evaluate LIM on various dynamic datasets, benchmarking against image-space interpolation methods (e.g., FiLM) and direct triplane linear interpolation, and demonstrate clear advantages. In summary, LIM is the first feed-forward model capable of high-speed tracked 4D asset reconstruction across diverse categories.

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