Visual Computing

Synthetic training significantly reduces the capture and annotation burden and in theory allows generation of an arbitrary amount of data.

We present a simple and effective method for removing noise and outliers from such point sets.

In this paper, we present an efficient algorithm to reconstruct intricate objects using densely sampled light fields.

We propose a new real-time temporal filtering and antialiasing (AA) method for rasterization graphics pipelines.

In this paper, we aim to retrieve sounds corresponding to a query image.

We propose a practical way to precompute and compactly store ASOs and demonstrate their ability to accelerate path tracing.

Our work on programmable animation texturing enhances the concept of texture mapping by letting artists stylize arbitrary animations using elementary animations, instantiated at the scale of their choice.

Effective composition in visual arts relies on the principle of movement, where the viewer’s eye is directed along subjective curves to a center of interest.

We present an algorithmic framework for the early classification of human intentions, and use it to accurately predict future human motions when planning the path of a robot in an environment that is shared with humans.

We present a novel method for synchronizing action videos where a similar action is performed by different people at different times and different locations with different local speed changes, e.g., as in sports like weightlifting, baseball pitch, or dance.