Human digitalization is required in many applications, such as AR/VR, robotics, games, and social networking. This course covers the core technologies required to model and simulate motions for digital humans and robotic characters. Topics include kinematic modeling, physics-based simulation, trajectory optimization, reinforcement learning, feedback control for motor skills, motion capture, data-driven motion synthesis, and ML-based generative models. They will be richly illustrated with examples.
The goal of this course is to provide students with a good understanding of computer vision and image analysis techniques. The main concepts and techniques will be studied in depth and practical algorithms and approaches will be discussed and explored through the exercises.
This seminar covers advanced topic in digital humans with a focus on the latest research results. Topics include estimating human pose and motion from images, human motion synthesis, learning-based human avatar creation, learning neural implicit representations for humans, modeling, animations, artificial intelligence for digital characters, and others. A collection of research papers is selected.
This seminar covers advanced topics in computer vision, such as 3D reconstruction, image understanding, object detection, people tracking, motion prediction, and other related topics. Each time the course is offered, a collection of research papers is selected and each student presents one paper to the class and leads a discussion about the paper and related topics.
In this doctoral seminar, current research at the Institute for Visual Computing will be presented and discussed. The goal is to learn about current research projects at our institute, to strengthen our expertise in the field, to provide a platform where research challenges caThis graduate seminar provides doctoral students in computer science a chance to read and discuss current research papers.
Human digitalization is required in many applications, such as AR/VR, robotics, games, and social networking. The course covers core techniques and fundamental tools necessary for perceiving and modeling humans. The main topics include human body modeling, human appearance and motion modeling, and human-scene interaction capture and modeling.
In this doctoral seminar, current research at the Institute for Visual Computing will be presented and discussed. The goal is to learn about current research projects at our institute, to strengthen our expertise in the field, to provide a platform where research challenges caThis graduate seminar provides doctoral students in computer science a chance to read and discuss current research papers.
This seminar covers advanced topics in computer graphics, such as modeling, rendering, animation, real-time graphics, physical simulation, and computational photography. Each time the course is offered, a collection of research papers is selected and each student presents one paper to the class and leads a discussion about the paper and related topics.
The goal of this course is to provide students with a good understanding of computer vision and image analysis techniques. The main concepts and techniques will be studied in depth and practical algorithms and approaches will be discussed and explored through the exercises.
In this doctoral seminar, current research at the Institute for Visual Computing will be presented and discussed. The goal is to learn about current research projects at our institute, to strengthen our expertise in the field, to provide a platform where research challenges caThis graduate seminar provides doctoral students in computer science a chance to read and discuss current research papers.
Recent developments in neural network (aka “deep learning”) have drastically advanced the performance of machine perception systems in a variety of areas including drones, self-driving cars and intelligent UIs. This course is a deep dive into details of the deep learning algorithms and architectures for a variety of perceptual tasks.
In this doctoral seminar, current research at the Institute for Visual Computing will be presented and discussed. The goal is to learn about current research projects at our institute, to strengthen our expertise in the field, to provide a platform where research challenges caThis graduate seminar provides doctoral students in computer science a chance to read and discuss current research papers.
This seminar covers advanced topics in computer graphics, such as modeling, rendering, animation, real-time graphics, physical simulation, and computational photography. Each time the course is offered, a collection of research papers is selected and each student presents one paper to the class and leads a discussion about the paper and related topics.
The goal of this course is to provide students with a good understanding of computer vision and image analysis techniques. The main concepts and techniques will be studied in depth and practical algorithms and approaches will be discussed and explored through the exercises.
In this doctoral seminar, current research at the Institute for Visual Computing will be presented and discussed. The goal is to learn about current research projects at our institute, to strengthen our expertise in the field, to provide a platform where research challenges caThis graduate seminar provides doctoral students in computer science a chance to read and discuss current research papers.
This project aims to build a system to capture interactions between people and the environment.
Supervisors: yan.zhang@inf.ethz.ch, kraus@ibk.baug.ethz.ch
This project attempts to learn object geometry and appearance from a set of 2D images and allows for scale specific controlling. We have also witnessed many great processes in realistic controllable 2D image synthesis and pleasant 3D image results by tacking leverage the recent advance in volume rendering. The core idea of this project is to extend the recent 3D generator that enables a level of control on both appearance and geometry.
Supervisors: anpei.chen@inf.ethz.ch
Supervisors: kkarunrat@inf.ethz.ch
This project attempts to reconstruct the geometric and appearance of 4D scenes (static scene + moving objects). We will start with decomposable radiance field reconstruction with a specific setting: a middle scale static environment (room or outdoor street) and one class of objects (human or car).
Supervisors: anpei.chen@inf.ethz.ch
Supervisors: Francis Engelmann (mailto:francisengelmann@ai.ethz.ch)
Supervisors: Shengyu Huang (shengyu.huang@geod.baug.ethz.ch), Xuyang Bai (xbaiad@connect.ust.hk), Dr. Theodora Kontogianni (theodora.kontogianni@inf.ethz.ch), Prof. Dr. Konrad Schindler (konrad.schindler@geod.baug.ethz.ch)