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Josh Patterson

dblp:87/9923 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2020
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1Graphics, computer vision, multimedia, augmented reality and games · 1Applied, interdisciplinary, general and emerging computing · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer graphics and multimedia
1 paper
Computational photography and imaging · 57% Rendering · 38% Image and video processing · 6%

Topics — the 6 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computational photography and imaging › 3d imaging
3d photography
0.412020
One shot 3D photography · ACM Trans. Graph. 2020
Computational photography and imaging
depth estimation
0.412020
One shot 3D photography · ACM Trans. Graph. 2020
Rendering
image-based rendering
0.412020
One shot 3D photography · ACM Trans. Graph. 2020
Rendering › image-based rendering
layered depth image
0.412020
One shot 3D photography · ACM Trans. Graph. 2020
Computational photography and imaging › depth estimation
monocular depth estimation
0.412020
One shot 3D photography · ACM Trans. Graph. 2020
Image and video processing › image restoration
image inpainting
0.112020
One shot 3D photography · ACM Trans. Graph. 2020

Methods — techniques the papers use, named apart from their topics

monocular depth estimation network · 0.4mobile optimization · 0.4inpainting network · 0.4
YearPublicationVenuePosition
2020 One shot 3D photography
abstract
3D photography is a new medium that allows viewers to more fully experience a captured moment. In this work, we refer to a 3D photo as one that displays parallax induced by moving the viewpoint (as opposed to a stereo pair with a fixed viewpoint). 3D photos are static in time, like traditional photos, but are displayed with interactive parallax on mobile or desktop screens, as well as on Virtual Reality devices, where viewing it also includes stereo. We present an end-to-end system for creating and viewing 3D photos, and the algorithmic and design choices therein. Our 3D photos are captured in a single shot and processed directly on a mobile device. The method starts by estimating depth from the 2D input image using a new monocular depth estimation network that is optimized for mobile devices. It performs competitively to the state-of-the-art, but has lower latency and peak memory consumption and uses an order of magnitude fewer parameters. The resulting depth is lifted to a layered depth image, and new geometry is synthesized in parallax regions. We synthesize color texture and structures in the parallax regions as well, using an inpainting network, also optimized for mobile devices, on the LDI directly. Finally, we convert the result into a mesh-based representation that can be efficiently transmitted and rendered even on low-end devices and over poor network connections. Altogether, the processing takes just a few seconds on a mobile device, and the result can be instantly viewed and shared. We perform extensive quantitative evaluation to validate our system and compare its new components against the current state-of-the-art.
Johannes Kopf 0001, Kevin Matzen, Suhib Alsisan, Ocean Quigley, Francis Ge, Yangming Chong, Josh Patterson, Jan-Michael Frahm, Matthew Yu, Peizhao Zhang, Peter Vajda, Ayush Saraf, Michael F. Cohen
ACM Trans. Graph.7
2009 TinyTermite: A Secure Routing Algorithm on Intel Mote 2 Sensor Network Platform
Mina Sartipi, Josh Patterson
IAAI2