7 papers
Learning Coupled System Dynamics under Incomplete Physical Constraints and Missing Data
Esha Saha, Hao Wang
Advances in data acquisition and computational methods have accelerated the use of differential equation based modelling for complex systems. Such systems are often described by co…
TerraGen: A Unified Multi-Task Layout Generation Framework for Remote Sensing Data Augmentation
Datao Tang, Hao Wang, Yudeng Xin +5
Remote sensing vision tasks require extensive labeled data across multiple, interconnected domains. However, current generative data augmentation frameworks are task-isolated, i.e.…
High-Fidelity Simulated Data Generation for Real-World Zero-Shot Robotic Manipulation Learning with Gaussian Splatting
Haoyu Zhao, Cheng Zeng, Linghao Zhuang +11
The scalability of robotic learning is fundamentally bottlenecked by the significant cost and labor of real-world data collection. While simulated data offers a scalable alternativ…
Learning Deformable Body Interactions With Adaptive Spatial Tokenization
Hao Wang, Yu Liu, Daniel Biggs +3
Simulating interactions between deformable bodies is vital in fields like material science, mechanical design, and robotics. While learning-based methods with Graph Neural Networks…
Generating Moving 3D Soundscapes with Latent Diffusion Models
Christian Templin, Yanda Zhu, Hao Wang
Spatial audio has become central to immersive applications such as VR/AR, cinema, and music. Existing generative audio models are largely limited to mono or stereo formats and cann…
StyleStudio: Text-Driven Style Transfer with Selective Control of Style Elements
Mingkun Lei, Xue Song, Beier Zhu +2
Text-driven style transfer aims to merge the style of a reference image with content described by a text prompt. Recent advancements in text-to-image models have improved the nuanc…