6 papers
Multi-Bandwidth Distribution Matching Distillation: On the Equivalence of Distribution Matching Distillation and Drifting Models
Jialin Zhu, Xing Liu, Feixiang He +1
Researchers are exploring effective one-step generative model continuously, and, Drifting Models (Deng et al., 2026), demonstrate great potential in one-step generation recently. T…
Graphical X Splatting (GraphiXS): A Graphical Model for 4D Gaussian Splatting under Uncertainty
Doğa Yılmaz, Jialin Zhu, Deshan Gong +1
We propose a new framework to systematically incorporate data uncertainty in Gaussian Splatting. Being the new paradigm of neural rendering, Gaussian Splatting has been investigate…
A Step to Decouple Optimization in 3DGS
Renjie Ding, Yaonan Wang, Min Liu +6
3D Gaussian Splatting (3DGS) has emerged as a powerful technique for real-time novel view synthesis. As an explicit representation optimized through gradient propagation among prim…
3D Student Splatting and Scooping
Jialin Zhu, Jiangbei Yue, Feixiang He +1
Recently, 3D Gaussian Splatting (3DGS) provides a new framework for novel view synthesis, and has spiked a new wave of research in neural rendering and related applications. As 3DG…
Learning Extremely High Density Crowds as Active Matters
Feixiang He, Jiangbei Yue, Jialin Zhu +4
Video-based high-density crowd analysis and prediction has been a long-standing topic in computer vision. It is notoriously difficult due to, but not limited to, the lack of high-q…
Seamless Satellite-image Synthesis
Jialin Zhu, Tom Kelly
We introduce Seamless Satellite-image Synthesis (SSS), a novel neural architecture to create scale-and-space continuous satellite textures from cartographic data. While 2D map data…