Generative image models offer a unique value by creating new images. Such images can be sharp super-resolution versions of existing images or even realistic-looking synthetic photographs. Generative Adversarial Networks (GANs) and their variants have demonstrated…
Fourier Feature Networks are an exciting new development in Computer Vision, and their use for modeling radiance fields has produced a range of impressive results at the meeting point of Computer Vision and Computer Graphics.…
In this talk, we will offer an entirely white-box interpretation of deep (convolutional) networks from the perspective of data compression and group invariance. We’ll show how modern deep-layered architectures, linear (convolutional) operators and nonlinear activations,…
Big data-driven deep learning has helped significantly improve the performance of visual tasks in the past few years, but it has also exhibited limitations in scalability and adaptation to real-world scenarios. Researchers and practitioners are…
Deep learning plus huge training data is a popular paradigm in computer vision. However, after a decade of growth, it’s time to revisit its strengths and weaknesses. Will there be a new trend in computer…
Big data-driven deep learning has helped significantly improve the performance of visual tasks in the past few years, but it has also exhibited limitations in scalability and adaptation to real-world scenarios. Researchers and practitioners are…
The limitations of big data-driven deep learning in scalability and adaptation to real-world scenarios hinder its practical applications. To address these limitations, it’s extremely important to develop architectures and algorithms that can capture the fundamentals…
Speakers: Hanwang Zhang, Professor, Nanyang Technological University Yuwang Wang, Senior Researcher, Microsoft Research Asia Shujian Yu, Professor, UiT – The Arctic University of Norway One of the critical shortcomings of big data-driven deep learning is…
As the Gaming and Entertainment industry has grown to encompass a global consumer base, digital content creators face mounting challenges in scaling to meet consumer demand. A new opportunity is emerging to provide artists, designers,…
Speaker: Katsushi Ikeuchi, Sr. Principal Research Manager, Microsoft Research Redmond Learning-from-Observation (LfO), a robot-teaching paradigm, aims to build a robot system that understands what humans do through a small number of human observations and map…
