4 citations · 12 across the 15 of their papers we have counts for
17 papers · 1 filter
ADELE - Adaptive Delaunay Grids for High-Fidelity Mesh-Native Reconstruction
Johannes Weidenfeller, Shaofei Wang, Philipp Fürnstahl +1
Meshes remain the most practical representation for geometry reasoning and integration into graphics pipelines, yet existing reconstruction methods struggle to produce high-quality…
MV-dVRK: A Multi-Viewpoint Benchmark for Spatial Surgical Perception
Guido Caccianiga, Sergey Prokudin, Yutong Chen +9
Large-scale training and refined optimization techniques have greatly improved sparse multi-view 3D reconstruction. Despite their relevance to surgery, such methods have never befo…
TAPVid-MV: A Benchmark for Tracking Any Point in 3D Across Multiple Views
Skanda Koppula, Frano Rajic, Abdullah Faiz Ur Rahman +9
Multi-camera systems are increasingly practical for robotics, AR/VR, and autonomous driving because complementary views reduce depth ambiguity and preserve visibility under occlusi…
GrowFields: Compositional 4D Neural Fields for Topology-Changing Plant Growth
Joaquin Gajardo, Michele Volpi, Marko Mihajlovic +3
Quantifying plant growth dynamics from sparse longitudinal 3D observations is fundamental for agriculture and plant sciences. Yet, plants pose unique challenges: they undergo intri…
Multi-View 3D Point Tracking
Frano Rajič, Haofei Xu, Marko Mihajlovic +7
We introduce the first data-driven multi-view 3D point tracker, designed to track arbitrary points in dynamic scenes using multiple camera views. Unlike existing monocular trackers…
Spline Deformation Field
Mingyang Song, Yang Zhang, Marko Mihajlovic +3
Trajectory modeling of dense points usually employs implicit deformation fields, represented as neural networks that map coordinates to relate canonical spatial positions to tempor…
DNF-Avatar: Distilling Neural Fields for Real-time Animatable Avatar Relighting
Zeren Jiang, Shaofei Wang, Siyu Tang
Creating relightable and animatable human avatars from monocular videos is a rising research topic with a range of applications, e.g. virtual reality, sports, and video games. Prev…
Relightable Full-Body Gaussian Codec Avatars
Shaofei Wang, Tomas Simon, Igor Santesteban +15
We propose Relightable Full-Body Gaussian Codec Avatars, a new approach for modeling relightable full-body avatars with fine-grained details including face and hands. The unique ch…
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…
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…
LaRa: Efficient Large-Baseline Radiance Fields
Anpei Chen, Haofei Xu, Stefano Esposito +2
Radiance field methods have achieved photorealistic novel view synthesis and geometry reconstruction. But they are mostly applied in per-scene optimization or small-baseline settin…
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…
Morphable Diffusion: 3D-Consistent Diffusion for Single-image Avatar Creation
Xiyi Chen, Marko Mihajlovic, Shaofei Wang +2
Recent advances in generative diffusion models have enabled the previously unfeasible capability of generating 3D assets from a single input image or a text prompt. In this work, w…
3DGS-Avatar: Animatable Avatars via Deformable 3D Gaussian Splatting
Zhiyin Qian, Shaofei Wang, Marko Mihajlovic +2
We introduce an approach that creates animatable human avatars from monocular videos using 3D Gaussian Splatting (3DGS). Existing methods based on neural radiance fields (NeRFs) ac…
IntrinsicAvatar: Physically Based Inverse Rendering of Dynamic Humans from Monocular Videos via Explicit Ray Tracing
Shaofei Wang, Božidar Antić, Andreas Geiger +1
We present IntrinsicAvatar, a novel approach to recovering the intrinsic properties of clothed human avatars including geometry, albedo, material, and environment lighting from onl…
ResFields: Residual Neural Fields for Spatiotemporal Signals
Marko Mihajlovic, Sergey Prokudin, Marc Pollefeys +1
Neural fields, a category of neural networks trained to represent high-frequency signals, have gained significant attention in recent years due to their impressive performance in m…