Garment Animation NeRF with Color Editing

TL;DR

This paper introduces a neural rendering method that synthesizes detailed garment animations directly from body motion data, enabling realistic, consistent, and editable garment visuals without explicit garment proxies.

Contribution

It presents a novel approach that infers garment dynamics from body motion and synthesizes animations with detailed wrinkles and occlusions, also supporting garment recoloring.

Findings

Outperforms existing neural rendering methods in garment detail quality.

Demonstrates generalization to unseen motions and views.

Enables effective garment color editing.

Abstract

Generating high-fidelity garment animations through traditional workflows, from modeling to rendering, is both tedious and expensive. These workflows often require repetitive steps in response to updates in character motion, rendering viewpoint changes, or appearance edits. Although recent neural rendering offers an efficient solution for computationally intensive processes, it struggles with rendering complex garment animations containing fine wrinkle details and realistic garment-and-body occlusions, while maintaining structural consistency across frames and dense view rendering. In this paper, we propose a novel approach to directly synthesize garment animations from body motion sequences without the need for an explicit garment proxy. Our approach infers garment dynamic features from body motion, providing a preliminary overview of garment structure. Simultaneously, we capture detailed features from synthesized reference images of the garment's front and back, generated by a pre-trained image model. These features are then used to construct a neural radiance field that renders the garment animation video. Additionally, our technique enables garment recoloring by decomposing its visual elements. We demonstrate the generalizability of our method across unseen body motions and camera views, ensuring detailed structural consistency. Furthermore, we showcase its applicability to color editing on both real and synthetic garment data. Compared to existing neural rendering techniques, our method exhibits qualitative and quantitative improvements in garment dynamics and wrinkle detail modeling. Code is available at \url{https://github.com/wrk226/GarmentAnimationNeRF}.