Research Community Services
2021
3DV 2021: Tutorial on the Advances in Neural Rendering
In this tutorial, we will talk about the advances in neural rendering, especially the underlying 2D and 3D representations that allow for novel viewpoint synthesis, controllability and editability. Specifically, we will discuss neural rendering methods based on 2D GANs, techniques using 3D Neural Radiance Fields or learnable sphere proxies. Besides methods that handle static content, we will talk about dynamic content as well.
2021, Nov 29 — [Video]SIGGRAPH 2021: Course on the Advances in Neural Rendering
This course covers the advances in neural rendering over the years 2020-2021.
2021, Aug 08 — [Video] [Bibtex]2020
CVPR 2020: Tutorial on Neural Rendering
Neural rendering is a new and rapidly emerging field that combines generative machine learning techniques with physical knowledge from computer graphics, e.g., by the integration of differentiable rendering into network training. This state-of-the-art report summarizes the recent trends and applications of neural rendering.
2020, Apr 08 — [Paper] [Video] [Bibtex]CVPR 2020: Workshop on Media Forensics
This CVPR workshop covers the advances on all fronts of media forensics: from detection of manipulations, biometric implications, misrepresentation/spoofing, etc.
2020, Apr 08 —2018
ECCV 2018: Tutorial on Face Tracking and its Applications
This invited tutorial is about monocular face tracking techniques and also discusses the possible applications. It is based on our Eurographics state-of-the-art report.
2018, Sep 08 — [Paper] [Bibtex]Eurographics 2018: State of the Art on Monocular 3D Face Reconstruction, Tracking, and Applications
This state-of-the-art report session summarizes recent trends in monocular facial performance capture and discusses its applications, which range from performance-based animation to real-time facial reenactment. We focus on methods where the central task is to recover and track a three dimensional model of the human face using optimization-based reconstruction algorithms.
2018, Apr 24 — [Paper] [Bibtex]