We present a real-time method for synthesizing highly complex human motions using a
novel training regime we call the auto-conditioned Recurrent Neural Network (acRNN) …

Synthesizing human motion with a global structure, such as a choreography, is a
challenging task. Existing methods tend to concentrate on local smooth pose transitions and …

Creating animation of a character putting on clothing is challenging due to the complex
interactions between the character and the simulated garment. We take a model-free deep …

We present ClothesNet: a large-scale dataset of 3D clothes objects with information-rich
annotations. Our dataset consists of around 4000 models covering 11 categories annotated …

Cloth dynamics plays an important role in the visual appearance of moving characters.
Properly accounting for contact and friction is of utmost importance to avoid cloth-body and …

Computer Graphics has a long history in the design of effective algorithms for handling
contact and friction between solid objects. For the sake of simplicity and versatility, most …

We propose an optimization-driven approach for automated, physics-based pattern design
for tight-fitting clothing. Designing such clothing poses particular challenges since large …

Pose Guided Person Image Generation (PGPIG) is the task of transforming a person's image
from the source pose to a target pose. Existing PGPIG methods often tend to learn an end-to …

We present a novel approach for manipulating high-DOE deformable objects such as cloth.
Our approach uses a random-forest-based controller that maps the observed visual features …

This paper introduces a new technique to synthesize dexterous manipulation of cloth. Given
a simple description of the desired cloth motion, our algorithm computes appropriate joint …