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By Robert Anderson, David Gallup, Jonathan T. Barron, Janne Kontkanen, Noah Snavely, Carlos Hernández, Sameer Agarwal, S. M. Seitz. 2016

194 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Signal Processing

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

In Signal Processing

Citations in the corpus

Deep visual foresight for planning robot motion (2016, methodology): “[40], an optical flow algorithm used in a large-scale production system.”
DeepView: View Synthesis With Learned Gradient Descent (2019, methodology): “We corrected exposure differences using a method similar to [4].”
Soft 3D reconstruction for view synthesis (2017, methodology): “With digital cameras continually decreasing in size and cost, and increasing demand for more immersive content (e.g. for VR/AR headsets), many new cameras and camera ‘rigs’ are being developed to capture images and video from several viewpoints simultaneously [Anderson et al. 2016; Cabral 2016].”
Deep blending for free-viewpoint image-based rendering (2018, background): “Recently, commercial systems [Anderson et al. 2016] 12 are able to deliver high-quality results by capturing data with a multi-camera rig and constraining the virtual viewpoint.”
SegFlow: Joint Learning for Video Object Segmentation and Optical Flow (2017, background): “Video analysis has attracted much attention in recent years due to the numerous vision applications, such as autonomous driving [15, 9, 33], video surveillance [40, 10, 20] and virtual reality [1].”
Saliency in VR: How Do People Explore Virtual Environments? (2016, background): “The experiences offered by these emerging systems are inherently different from radio, television, or theater, opening new directions in research areas such as cinematic VR capture [1], interaction [53], or content generation and editing [39, 49].”