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Data-driven methods for physical simulation are an attractive option for interactive applications due to their ability to trade precomputation and memory footprint in exchange for improved runtime performance. Yet, existing data-driven methods fall ...

The depiction of motion in static representations has a long tradition in art and science alike. Often, motion is depicted by spatio-temporal summarizations that try to preserve as much information of the original dynamic content as possible. In our ...

We present a novel framework that consists of two-level regressors for finding correlations between human shapes and landmark positions in both body part and holistic scales. To this end, we first develop pose invariant coordinates of landmarks that ...

We present a real-time deep learning framework for video-based facial performance capture---the dense 3D tracking of an actor's face given a monocular video. Our pipeline begins with accurately capturing a subject using a high-end production facial ...

Efficient learning of 3D character control still remains an open problem despite of the remarkable recent advances in the field. We propose a new algorithm that combines planning by a sampling-based model-predictive controller and learning from the ...

The use of deep reinforcement learning allows for high-dimensional state descriptors, but little is known about how the choice of action representation impacts learning and the resulting performance. We compare the impact of four different action ...

Over the years, the ACM SIGGRAPH / Eurographics Symposium on Computer Animation (SCA) has established itself as the leading conference for research in Computer Animation. In this 16th edition, SCA aimed to further broaden the horizon of computer ...

Normal estimation in point clouds is a crucial first step for numerous algorithms, from surface reconstruction and scene understanding to rendering. A recurrent issue when estimating normals is to make appropriate decisions close to sharp features, not ...

Given the increasing availability of high-resolution input data, today's computer vision problems tend to grow beyond what has been considered tractable in the past. This is especially true for Markov Random Fields (MRFs), which have expanded beyond ...

Properties of granular materials or molecular structures are often studied on a simple geometric model - a set of 3D balls. If the balls simultaneously change in size by a constant speed, topological properties of the empty space outside all these balls ...

Conformal maps between planar domains are an important tool in geometry processing, used for shape deformation and image warping. The Riemann mapping theorem guarantees that there exists a conformal map between any two simply connected planar domains, ...

This paper targets two related color manipulation problems: Color transfer for modifying an image's colors and colorization for adding colors to a grayscale image. Automatic methods for these two applications propose to modify the input image using a ...

We present a data driven model of eye movement, that includes movement of the globes, the periorbital soft tissues and eyelids and also the formation of wrinkles in the tissues. We describe a pipeline for measurement and estimation of tissue movement ...

The shadow theatre is an unique performing arts, which utilizes a shadow as an main communication tool. This can be understood easily by an extension of traditional shadow play. Key difference comes from the fact that entire human bodies are used to ...

All approaches to simulating human collision avoidance for virtual crowds make simplifications to the underlying behaviour. One of the prevalent simplifications is to ignore it's holonomic aspect (i.e. sidestepping, walking backwards). This does not, ...

The interpretation of user sketches generates research interest in the product design community since the computer interpretation of sketches may reduce the design-to-market time while giving the designer greater flexibility and control of the design ...

Hyperparameters are among the most crucial factors that affect the performance of machine learning algorithms. In general, there is no direct method for determining a set of satisfactory parameters, so hyperparameter search needs to be conducted each ...

Recently there has been a growing interest in sketch recognition technologies for facilitating human-computer interaction. Existing sketch recognition studies mainly focus on recognizing pre-defined symbols and gestures. However, just as there is a need ...

Lighting plays a major role in photography. Professional photographers use elaborate installations to light their subjects and achieve sophisticated styles. However, lighting moving subjects performing dynamic tasks presents significant challenges and ...

We present a system for real-time, high-resolution, sparse voxelization of an image-based surface model. Our approach consists of a coarse-to-fine voxel representation and a collection of parallel processing steps. Voxels are stored as a list of ...