Trajectory prediction has been widely pursued in many fields, and many model-based and
model-free methods have been explored. The former include rule-based, geometric or …

Differentiable simulators continue to push the state of the art across a range of domains
including computational physics, robotics, and machine learning. Their main value is the …

Abstract 3D reconstruction of dynamic scenes is a long-standing problem in computer
graphics and increasingly difficult the less information is available. Shape-from-Template …

We investigate a new task in human motion prediction which is predicting motions under
unexpected physical perturbation potentially involving multiple people. Compared with …

We propose a new method for cloth digitalization. Deviating from existing methods which
learn from data captured under relatively casual settings we propose to learn from data …

Human trajectory forecasting helps to understand and predict human behaviors, enabling
applications from social robots to self-driving cars, and therefore has been heavily …

The 39-volume set, comprising the LNCS books 13661 until 13699, constitutes the refereed
proceedings of the 17th European Conference on Computer Vision, ECCV 2022, held in Tel …

We investigate the capabilities of neural inverse procedural modeling to infer high-quality
procedural yarn models with fiber-level details from single images of depicted yarn samples …

The slub denim has various appearance styles that attract consumers due to the irregular
distribution and long cycle of the slubs in the slub yarn. This characteristic of the slub yarn …

Differentiable simulators continue to push the state of the art across a range of domains
including computational physics, robotics, and machine learning. Their main value is the …