Generating Audiovisual Synergy Fluid Animation for Highly Immersive VR Experience
Na Jiang, Xiangcheng Zhai, Yuxuan Qiu, Xiaohui Tan, Aimin Hao, Yang Gao
摘要
Generative content is increasingly applied in VR to provide immersive experiences, yet maintaining high generation quality remains challenging for audiovisual effects. Particularly in dynamic fluid phenomena, achieving realism and presence requires adherence to physical laws. To accomplish this objective, this work proposes an audiovisual synergy fluid animation generation framework, which enhances immersion by improving motion texture fidelity and audiovisual consistency. It comprises Detail-Enhanced Texture generator (DET) and Physics-Guided Audio generator (PGA). DET integrates Global-Local Physics guidance (GLP) and Temporal Texture Modeling (TTM) to produce video textures, explicitly optimizing dynamic details by leveraging local motion cues and assigned cumulative differences. PGA incorporates Visual Semantic Augmenter (VSA) and Rhythm Semantic Adapter (RSA) to synchronize audio by fusing static visual semantics with dynamic motion semantics to improve temporal coherence. By integrating DET and PGA, this framework strengthens audiovisual immersion in VR natural dynamic scenes from both visual and auditory perspectives. Quantitative and qualitative evaluations demonstrate that our approach surpasses most existing methods in terms of texture realism and audiovisual synchronization, offering new insights for advancing immersive experiences in dynamic VR phenomena.
问问这篇 Paper
问问你的智能体。
Lune 读过与它相关的顶会 Paper,每个回答都会注明依据哪几篇。
相关 Paper
- ImmerseGen: Agent-Guided Immersive World Generation with Alpha-Textured ProxiesJinyan Yuan, Bangbang Yang, Keke Wang, Panwang Pan 等IEEE VR 2026 · 被引用 2 次
- Physical Simulator In-the-Loop Video GenerationLin Geng Foo, Mark He Huang, Alexandros Lattas, Stylianos Moschoglou 等CVPR 2026 · 被引用 13 次
- ANFluid: Animate Natural Fluid Photos base on Physics-Aware Simulation and Dual-Flow Texture LearningXiangcheng Zhai, Yingqi Jie, Xueguang Xie, Aimin Hao 等ACM MM 2024 · 被引用 4 次
- Sonic4D: Spatial Audio Generation for Immersive 4D Scene ExplorationSiyi Xie, Hanxin Zhu, Xinyi Chen, Tianyu He 等AAAI 2026 · 被引用 4 次
- -AVAS: Can Physics-Integrated Audio-Visual Modeling Boost Neural Acoustic Synthesis?Susan Liang, Chao Huang, Yunlong Tang, Zeliang Zhang 等ICCV 2025 · 被引用 4 次
