48 citations · 59 across the 13 of their papers we have counts for
5 papers · 1 filter
SplatFormer: Point Transformer for Robust 3D Gaussian Splatting
Yutong Chen, Marko Mihajlovic, Xiyi Chen +3
3D Gaussian Splatting (3DGS) has recently transformed photorealistic reconstruction, achieving high visual fidelity and real-time performance. However, rendering quality significan…
RISE-SDF: a Relightable Information-Shared Signed Distance Field for Glossy Object Inverse Rendering
Deheng Zhang, Jingyu Wang, Shaofei Wang +4
In this paper, we propose a novel end-to-end relightable neural inverse rendering system that achieves high-quality reconstruction of geometry and material properties, thus enablin…
FreSh: Frequency Shifting for Accelerated Neural Representation Learning
Adam Kania, Marko Mihajlovic, Sergey Prokudin +2
Implicit Neural Representations (INRs) have recently gained attention as a powerful approach for continuously representing signals such as images, videos, and 3D shapes using multi…
SplatFields: Neural Gaussian Splats for Sparse 3D and 4D Reconstruction
Marko Mihajlovic, Sergey Prokudin, Siyu Tang +4
Digitizing 3D static scenes and 4D dynamic events from multi-view images has long been a challenge in computer vision and graphics. Recently, 3D Gaussian Splatting (3DGS) has emerg…
Degrees of Freedom Matter: Inferring Dynamics from Point Trajectories
Yan Zhang, Sergey Prokudin, Marko Mihajlovic +2
Understanding the dynamics of generic 3D scenes is fundamentally challenging in computer vision, essential in enhancing applications related to scene reconstruction, motion trackin…