2 citations · 3 across the 11 of their papers we have counts for
13 papers
Omni-RS: Unifying Multi-Task Understanding and Generation in Remote Sensing
Pan Yin. Shuai Yang, Pan Yin, Yuanhao Liu +8
Practical remote sensing applications often require both understanding and generation capabilities for the same geographic scene. However, most existing methods address either unde…
PhysWave: Physics-Guided Latent Diffusion Models for Controllable Spatial Audio Generation
Lingfeng Yao, Chenpei Huang, Xingke Yang +5
Text-to-spatial audio generation, such as text-to-First-Order Ambisonics (FOA), provides a convenient way to create spatial audio for billion-dollar gaming and film industries. How…
VLM-Guided Group Preference Alignment for Diffusion-based Human Mesh Recovery
Wenhao Shen, Hao Wang, Wanqi Yin +5
Human mesh recovery (HMR) from a single RGB image is inherently ambiguous, as multiple 3D poses can correspond to the same 2D observation. Recent diffusion-based methods tackle thi…
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…
Efficient Physics Simulation for 3D Scenes via MLLM-Guided Gaussian Splatting
Haoyu Zhao, Hao Wang, Xingyue Zhao +4
Recent advancements in 3D generation models have opened new possibilities for simulating dynamic 3D object movements and customizing behaviors, yet creating this content remains ch…
Topology-aware Human Avatars with Semantically-guided Gaussian Splatting
Haoyu Zhao, Chen Yang, Hao Wang +2
Reconstructing photo-realistic and topology-aware animatable human avatars from monocular videos remains challenging in computer vision and graphics. Recently, methods using 3D Gau…
3D-Consistent Human Avatars with Sparse Inputs via Gaussian Splatting and Contrastive Learning
Haoyu Zhao, Hao Wang, Chen Yang +1
Existing approaches for human avatar generation--both NeRF-based and 3D Gaussian Splatting (3DGS) based--struggle with maintaining 3D consistency and exhibit degraded detail recons…
SciPostLayout: A Dataset for Layout Analysis and Layout Generation of Scientific Posters
Shohei Tanaka, Hao Wang, Yoshitaka Ushiku
Scientific posters are used to present the contributions of scientific papers effectively in a graphical format. However, creating a well-designed poster that efficiently summarize…