The PIXL lunch meets every Monday during the semester at noon in
room 402 of the Computer Science building. To get on the mailing
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Monday, September 23, 2019
Hyperparameter Optimization in Black-box Image Processing using Differentiable Proxies
Ethan Tseng and Felix Yu
Todays cameras rely on proprietary black-box image processing units with manually tuned parameters. This work presents a fully automatic approach to optimize these black-box systems using stochastic first-order optimization.
Monday, September 30, 2019
Association and Imagination
When you see the sunset standing on Seine river in Paris, you can trivially imagine it along the Monongahela in Pittsburgh. When you hear something, you can easily imagine how someone would have said it. When you think of an event from the past, you can relive every bit of it in your imagination. Humans have remarkable abilities to associate different concepts and create visual worlds far beyond what could be seen by a human eye, including inferring the state of unobserved, imagining the unknown, and thinking about diverse possibilities about what lies in the future. These human powers require minimal instructions and primarily relies on observation and interaction with a dynamic environment. The simple tasks from daily life that are trivial for humans to think and imagine have remained challenging for machine perception and artificial intelligence. The inability to associate and a lack of sense of imagination in machines substantially restricts their applicability.
In this talk, I will demonstrate how thinking about association at various levels of abstraction can lead to machine imagination. I will present algorithms that enable association between different domains in an unsupervised manner. This ability to associate allows automatic creation of audio and visual content (images, videos, 4D space-time visualization of dynamic events) that is also user-controllable and interactive. I will show diverse user applications in audio-visual data retargeting, reconstruction, synthesis, and manipulation. These applications are the first steps towards building machines with a powerful audio-visual simulator that will enable them to imagine complex hypothetical situations, and model the aspects of their surroundings that is not easily perceived.
Aayush Bansal is a PhD candidate at the Robotics Institute of Carnegie Mellon University. He is a recipient of Uber Presidential Fellowship (2016-17), Qualcomm Fellowship (2017-18), and Snap Fellowship (2019-20). The production houses such as BBC Studios and PBS are using his research work to create documentaries and short movies. Various national and international media such as NBC, CBS, France TV, and The Journalist have extensively covered his work.
No talks scheduled yet.