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grail.cs.washington.edu | ||
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peizhuoli.github.io
We present GANimator, a generative model that learns to synthesize novel motions from a single, short motion sequence. GANimator generates motions that resemble the core elements of the original motion, while simultaneously synthesizing novel and diverse movements. It also enables applications including crowd simulation, key-frame editing, style transfer, and interactive control for a variety of skeletal structures e.g., bipeds, quadropeds, hexapeds, and more, all from a single input sequence. |
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graphics.cs.utah.edu
[AI summary] The blog post introduces a new adaptive level-of-detail technique for hardware-accelerated ray tracing that significantly reduces energy use and render time by dynamically adjusting mesh resolution per ray. |
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www.matthewtancik.com
A method for synthesizing novel views of complex scenes by optimizing an underlying continuous volumetric scene function using a sparse set of input views. |
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bryanbrattlof.com
Developing our first neural network with Keras |
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