Analysis and synthesis of human motion is a challenging task in computer vision and graphics. The emerging power of deep learning tools paves the way to a fascinating research path the enable intuitive motion editing in videos and manipulation of motion of 3D characters. Have you ever been amazed by the quality and realism of characters motion in movies and video games? Do you wonder how motion can be captured and modeled? How deep learning and data-driven approaches may assist with that? You can find the answers to these questions in Kfir's talk.
Kfir Aberman is a research scientist at the Reality Capture Group in the Beijing Film Academy, where he creates innovative solutions to core technological problem related to the film industry. Kfir received his Ph.D. from Tel-Aviv University where he worked with Prof. Daniel Cohen-Or on various topics related to computer graphics. Kfir has extensive experience in developing and training deep networks for synthesis of visual content such as images, videos, and 3D characters.