9 citations · 16 across the 7 of their papers we have counts for
9 papers
Continuous Levels of Detail for Light Field Networks
David Li, Brandon Y. Feng, Amitabh Varshney
Recently, several approaches have emerged for generating neural representations with multiple levels of detail (LODs). LODs can improve the rendering by using lower resolutions and…
3D Motion Magnification: Visualizing Subtle Motions with Time Varying Radiance Fields
Brandon Y. Feng, Hadi Alzayer, Michael Rubinstein +2
Motion magnification helps us visualize subtle, imperceptible motion. However, prior methods only work for 2D videos captured with a fixed camera. We present a 3D motion magnificat…
Learning to Estimate 6DoF Pose from Limited Data: A Few-Shot, Generalizable Approach using RGB Images
Panwang Pan, Zhiwen Fan, Brandon Y. Feng +3
The accurate estimation of six degrees-of-freedom (6DoF) object poses is essential for many applications in robotics and augmented reality. However, existing methods for 6DoF pose…
Seeing the World through Your Eyes
Hadi Alzayer, Kevin Zhang, Brandon Feng +2
The reflective nature of the human eye is an underappreciated source of information about what the world around us looks like. By imaging the eyes of a moving person, we can collec…
View Correspondence Network for Implicit Light Field Representation
Süleyman Aslan, Brandon Yushan Feng, Amitabh Varshney
We present a novel technique for implicit neural representation of light fields at continuously defined viewpoints with high quality and fidelity. Our implicit neural representatio…
StegaNeRF: Embedding Invisible Information within Neural Radiance Fields
Chenxin Li, Brandon Y. Feng, Zhiwen Fan +2
Recent advances in neural rendering imply a future of widespread visual data distributions through sharing NeRF model weights. However, while common visual data (images and videos)…