81 citations · 103 across the 6 of their papers we have counts for
16 papers · 1 filter
HyperNeRF: A Higher-Dimensional Representation for Topologically Varying Neural Radiance Fields
Keunhong Park, Utkarsh Sinha, Peter Hedman +5
Neural Radiance Fields (NeRF) are able to reconstruct scenes with unprecedented fidelity, and various recent works have extended NeRF to handle dynamic scenes. A common approach to…
Repopulating Street Scenes
Yifan Wang, Andrew Liu, Richard Tucker +4
We present a framework for automatically reconfiguring images of street scenes by populating, depopulating, or repopulating them with objects such as pedestrians or vehicles. Appli…
Real-Time High-Resolution Background Matting
Shanchuan Lin, Andrey Ryabtsev, Soumyadip Sengupta +3
We introduce a real-time, high-resolution background replacement technique which operates at 30fps in 4K resolution, and 60fps for HD on a modern GPU. Our technique is based on bac…
Animating Pictures with Eulerian Motion Fields
Aleksander Holynski, Brian Curless, Steven M. Seitz +1
In this paper, we demonstrate a fully automatic method for converting a still image into a realistic animated looping video. We target scenes with continuous fluid motion, such as…
Nerfies: Deformable Neural Radiance Fields
Keunhong Park, Utkarsh Sinha, Jonathan T. Barron +4
We present the first method capable of photorealistically reconstructing deformable scenes using photos/videos captured casually from mobile phones. Our approach augments neural ra…
Reconstructing NBA Players
Luyang Zhu, Konstantinos Rematas, Brian Curless +2
Great progress has been made in 3D body pose and shape estimation from a single photo. Yet, state-of-the-art results still suffer from errors due to challenging body poses, modelin…