SplatFormer: Point Transformer for Robust 3D Gaussian Splatting
Yutong Chen, Marko Mihajlovic, Xiyi Chen, Yiming Wang, Sergey Prokudin, Siyu Tang
arXiv, 2025
project page / arXiv / code

SplatFormer is a data-driven 3D transformer for refining 3D Gaussian splats to improve quality of novel views from extreme camera viewpoints.

FreSh: Frequency Shifting for Accelerated Neural Representation Learning
Adam Kania, Marko Mihajlovic, Sergey Prokudin, Jacek Tabor, Przemysław Spurek
arXiv, 2025
project page / arXiv / code / colab

FreSh aligns the frequencies of an implicit neural representation with its target signal to speed up the convergence.

RISE-SDF: A Relightable Information-Shared Signed Distance Field for Glossy Object Inverse Rendering
Deheng Zhang*, Jingyu Wang*, Shaofei Wang, Marko Mihajlovic, Sergey Prokudin, Hendrik P.A. Lensch, Siyu Tang
3DV, 2025
project page / arXiv / code

RISE-SDF reconstructs the geometry and material of glossy objects while achieving high-quality relighting.

SplatFields: Neural Gaussian Splats for Sparse 3D and 4D Reconstruction
Marko Mihajlovic, Sergey Prokudin, Siyu Tang, Robert Maier, Federica Bogo, Tony Tung, Edmond Boyer
ECCV, 2024
project page / arXiv / code

SplatFields regularizes 3D gaussian splats for sparse 3D and 4D reconstruction.

Morphable Diffusion: 3D-Consistent Diffusion for Single-image Avatar Creation
Xiyi Chen, Marko Mihajlovic, Shaofei Wang, Sergey Prokudin, Siyu Tang
CVPR, 2024
project page / arXiv / code

Morphable diffusion enables consistent controllable novel view synthesis of humans from a single image.

3DGS-Avatar: Animatable Avatars via Deformable 3D Gaussian Splatting
Zhiyin Qian, Shaofei Wang, Marko Mihajlovic, Andreas Geiger, Siyu Tang
CVPR, 2024
project page / arXiv / code

Given a monocular video, 3DGS-Avatar learns a clothed human avatars with short training time and interactive rendering frame rate.

Inferring Dynamics from Point Trajectories
Yan Zhang, Sergey Prokudin, Marko Mihajlovic, Qianli Ma, Siyu Tang
CVPR, 2024
project page / arXiv / code / video

How to infer scene dynamics from sparse point trajectory observations? We show a simple yet effective solution using a spatiotemporal MLP with carefully designed regularizations. No need for scene-specific priors.

ResFields: Residual Neural Fields for Spatiotemporal Signals
Marko Mihajlovic, Sergey Prokudin, Marc Pollefeys, Siyu Tang
ICLR (spotlight), 2024
project page / arXiv / code / colab / openreview

ResField layers incorporates time-dependent weights into MLPs to effectively represent complex temporal signals.

KeypointNeRF: Generalizing Image-based Volumetric Avatars using Relative Spatial Encoding of Keypoints
Marko Mihajlovic, Aayush Bansal, Michael Zollhoefer, Siyu Tang, Shunsuke Saito
ECCV, 2022
project page / arXiv / code / video

KeypointNeRF is a generalizable neural radiance field for virtual avatars. Given as input 2-3 images, KeypointNeRF generates volumetric radiance representation that can be rendered from novel views.

COAP: Compositional Articulated Occupancy of People
Marko Mihajlovic, Shunsuke Saito, Aayush Bansal, Michael Zollhoefer, Siyu Tang
CVPR, 2022
project page / arXiv / code / video

COAP is a novel neural implicit representation for articulated human bodies that provides an efficient mechanism for modeling self-contact and interactions with the environment.

MetaAvatar: Learning Animatable Clothed Human Models from Few Depth Images
Shaofei Wang, Marko Mihajlovic, Qianli Ma, Andreas Geiger, Siyu Tang
NeurIPS, 2021
project page / arXiv / code / video

Generalizable and controllable neural signed distance fields (SDFs) that represent clothed humans from monocular depth observations.

LEAP: Learning Articulated Occupancy of People
Marko Mihajlovic, Yan Zhang, Michael J. Black, Siyu Tang
CVPR, 2021
project page / arXiv / code / video

LEAP is a neural network architecture for representing volumetric animatable human bodies. It follows traditional human body modeling techniques and leverages a statistical human prior to generalize to unseen humans.

DeepSurfels: Learning Online Appearance Fusion
Marko Mihajlovic, Silvan Weder, Marc Pollefeys, Martin R. Oswald
CVPR, 2021
project page / arXiv / code / video

DeepSurfels is a novel 3D representation for geometry and appearance information that combines planar surface primitives with voxel grid representation for improved scalability and rendering quality.