Subspace Clothing Simulation Using Adaptive Bases

We present a new approach to clothing simulation using low-dimensional linear subspaces with temporally adaptive bases. Our method exploits full-space simulation training data in order to construct a pool of low-dimensional bases distributed across pose space. For this purpose, we interpret the simulation data as offsets from a kinematic deformation model that captures the global shape of clothing due to body pose.

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Efficient Simulation of Secondary Motion in Rig-Space

We present an efficient method for augmenting keyframed character animations with physically-simulated secondary motion. Our method achieves a performance improvement of one to two orders of magnitude over previous work without compromising on quality.

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Hierarchical Motion Brushes for Animation Instancing

Our work on “motion brushes” provides a new workflow for the creation and reuse of 3D animation with a focus on stylized movement and depiction. Conceptually, motion brushes expand existing brush models by incorporating hierarchies of 3D animated content including geometry, appearance information, and motion data as core brush primitives that are instantiated using a painting interface.

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Generating and Ranking Diverse Multi-Character Interactions

Our novel `generate-and-rank' approach rapidly and semi-automatically generates data-driven fight scenes from high-level text descriptions composed of simple clauses and phrases. From a database of captured motions and its associated motion graph, we first generate a `cascade' of plausible scenes.

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Facial Performance Enhancement Using Dynamic Shape Space Analysis

We present a technique for adding fine-scale details and expressiveness to low-resolution art-directed facial performances, such as those created manually using a rig, via marker-based capture, by fitting a morphable model to a video, or through Kinect reconstruction using recent faceshift technology.

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