25.09.2024: [New] One paper accepted at NeurIPS 2024:
10.09.2024: Invited Tutorial at GCPR 2024 on Virtual Humans and Quantum-enhanced Computer Vision (QeCV) by M. Habermann and myself. The slides on Quantum-enhanced Computer Vision can be accessed here.
04.09.2024: Invited lecture on Quantum-Enhanced Computer Vision at the 3rd European Summer School on Quantum AI (EQAI 2024).
17.06.2024: Keynote speaker at the Physics Based Vision meets Deep Learning (PBDL) Workshop at CVPR 2024.
31.05.2024: Invited talk at 3D Vision Summer School (3DVSS) 2024.
15.04.2024: We are co-organising two workshops at ECCV 2024. More details coming soon!
- TradiCV: 2nd Workshop on Traditional CV in the Age of Deep Learning
- Quantum Computer Vision and Machine Learning (QCVML) Workshop (2nd Edition)
25.03.2024: We contributed two state-of-the-art reports at EUROGRAPHICS'24:
- Po, Yifan, Golyanik et al. State of the Art on Diffusion Models for Visual Computing.
- Yunus et al. Recent Trends in 3D Reconstruction of General Non-Rigid Scenes.
08.03.2024: We released UnrealEgo Benchmark for stereo egocentric 3D human pose estimation!
01.03.2024: Papers accepted at CVPR 2024:
16.10.2023: Papers accepted at 3DV 2024:
- 3D Pose Estimation of Two Interacting Hands from a Monocular Event Camera (Spotlight).
- Quantum-Hybrid Stereo Matching With Nonlinear Regularization and Spatial Pyramids.
- SceNeRFlow: Time-Consistent Reconstruction of General Dynamic Scenes.
- ROAM: Robust and Object-aware Motion Generation using Neural Pose Descriptors.
- MACS: Mass-Conditioned 3D Hand and Object Motion Synthesis.
15.09.2023: 4DQV/VCAI contributed two journal and one conference proceedings papers to SIGGRAPH Asia 2023:
25.08.2023: We are organising a seminar on Quantum Computer Vision and Machine Learning (QCVML) (3CP) in WiSe 23/24.
18.08.2023: We are organising a lecture on Advanced Topics in Neural Rendering and 3D Reconstruction (3CP) in WiSe 23/24.
03.03.2023: Five papers at CVPR 2023 in Vancouver. Many thanks to all students, interns and collaborators!
- EventNeRF: Neural Radiance Fields from a Single Colour Event Camera.
- MoFusion: A Framework for Denoising-Diffusion-based Motion Synthesis (CVPR Highlight)
- Self-supervised Pre-training with Masked Shape Prediction for 3D Scene Understanding.
- Quantum Multi-Model Fitting (CVPR Highlight).
- CCuantuMM: Cycle-Consistent Quantum-Hybrid Matching of Multiple Shapes.
31.01.2023: We will organise the CVMLCG Seminar 2023.
21.01.2023: A paper on quantum annealing with machine learning is accepted at ICLR 2023 as Spotlight.
22.12.2022: A state of the art report (STAR) conditionally accepted at EUROGRAPHICS 2023.
16.12.2022: We are going to organise a Workshop on Quantum Computer Vision and Machine Learning at CVPR 2023; in collaboration with Tongyang Li, Jan-Nico Zaech, Martin Danelljan, Jacob Biamonte and Tolga Birdal. More details coming soon.
13.12.2022: Two articles conditionally accepted at EUROGRAPHICS 2023.
08.12.2022: V. Golyanik gave a talk titled Advances in Quantum Computer Vision at the Workshop on Quantum Information at Saarland University (event poster). The slides can be found here. Many thanks to the organisers for making such an event happen!
21.10.2022: An article on random number generation on quantum annealers accepted at IEEE Access.
05.10.2022: The source code of MoCapDeform is now available here: GitHub link.
30.09.2022: A paper on high-fidelity 3D human performance capture accepted at BMVC 2022.
12.09.2022: MoCapDeform received Best Student Paper Award at 3DV 2022.
05.08.2022: A paper on global 3D human motion capture (MoCapDeform) accepted at 3DV 2022.
25.07.2022: 4DQV will present several papers at ECCV 2022:
04.07.2022: The source code of Physical Inertial Poser (PIP) is now available here: GitHub link.
27.06.2022: The source code of φ-SfT ist now available here: GitHub link.
21.04.2022: The source code of Neural PhysCap is now available via GitHub.
19.02.2022: We are co-organising a tutorial associated with our STAR on Advances in Neural Rendering on the 27th of April at EUROGRAPHICS'22.
28.03.2022: 4DQV will present three papers at CVPR 2022:
11.02.2022: State of the art report on neural rendering (the updated version) accepted at EUROGRAPHICS'22.
25.10.2021: The source code of Convex Joint Graph Matching and Clustering via Semidefinite Relaxations is released.
18.10.2021: An article is accepted at TPAMI (HandVoxNet++).
17.10.2021: Two papers accepted at 3DV 2021 (about graph matching and clustering and human image generation).
13.10.2021: EventHands is mentioned in ICCV 2021 Daily.
12.10.2021: The source code of GraviCap is released on GitHub
11.10.2021: The source code of Q-Match is released on GitHub.
27.09.2021: The source code of EventHands is released on GitHub.
08.09.2021: Dennis Willsch gave a 4DQV Lecture Series talk titled Applications on Quantum Annealers at Jülich Supercomputing Centre. The video can be found here.
19.08.2021: We are going to present the following works at ICCV 2021: GraviCap, Non-Rigid Neural Radiance Fields, Iterative Shape Matching via Quantum Annealing and EventHands.
05.07.2021: The source code of PhysCap is now available here.
Welcome to the web page of the 4D and Quantum Vision (4DQV) group led by Dr. Vladislav Golyanik.
The focus of our team lies on 3D reconstruction and analysis of general deformable scenes, 3D reconstruction of the human body and matching problems on point sets and graphs. We are interested in neural approaches (both supervised and unsupervised), physics-based methods as well as new hardware and sensors (e.g., quantum computers and event cameras). We are integrated in the Visual Computing and Artificial Intelligence Department (D6) and working closely with Prof. Christian Theobalt.
Many research questions at the intersection of computer graphics, computer vision and machine learning involve challenging search problems (e.g., graph matching) or the optimisation of non-convex objectives. For such problems, we develop new algorithmic formulations that can be solved on modern adiabatic quantum annealers or universal quantum computers and investigate which advantages these approaches offer compared to existing classical methods.
Our reserach interests include (but are not limited to):
Dr. Vladislav Golyanik [personal page] [e-mail]