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In Proceedings of the 24th Annual Conference on Computer Graphics and Interactive Techniques (SIGGRAPH '97). Tour into the Picture: Using a Spidery Mesh Interface to Make Animation from a Single Image. Youichi Horry, Ken-Ichi Anjyo, and Kiyoshi Arai.Peter Hedman, Suhib Alsisan, Richard Szeliski, and Johannes Kopf.In International Conference on Computer Vision (ICCV). Digging into Self-Supervised Monocular Depth Prediction.
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Clément Godard, Oisin Mac Aodha, Michael Firman, and Gabriel J.In IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Unsupervised Monocular Depth Estimation with Left-Right Consistency. Clément Godard, Oisin Mac Aodha, and Gabriel J.Unsupervised CNN for Single View Depth Estimation: Geometry to the Rescue. Ravi Garg, Vijay Kumar B.G., Gustavo Carneiro, and Ian Reid.In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR). DeepView: View Synthesis With Learned Gradient Descent. John Flynn, Michael Broxton, Paul Debevec, Matthew DuVall, Graham Fyffe, Ryan Overbeck, Noah Snavely, and Richard Tucker.Cartographica: The International Journal for Geographic Information and Geovisualization 10 (1973), 112-122. Algorithms for the Reduction of the Number of Points Required to Represent a Digitized Line or Its Caricature. Springer-Verlag TELOS, Santa Clara, CA, USA. Computational Geometry: Algorithms and Applications (3rd ed. Mark de Berg, Otfried Cheong, Marc van Kreveld, and Mark Overmars.ChamNet: Towards Efficient Network Design Through Platform-Aware Model Adaptation. Jha, Peizhao Zhang, Bichen Wu, Hongxu Yin, Fei Sun, Yanghan Wang, and et al. Xiaoliang Dai, Yangqing Jia, Peter Vajda, Matt Uyttendaele, Niraj K.of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). The Cityscapes Dataset for Semantic Urban Scene Understanding. Marius Cordts, Mohamed Omran, Sebastian Ramos, Timo Rehfeld, Markus Enzweiler, Rodrigo Benenson, Uwe Franke, Stefan Roth, and Bernt Schiele.Pact: Parameterized clipping activation for quantized neural networks. Jungwook Choi, Zhuo Wang, Swagath Venkataramani, Pierce I-Jen Chuang, Vijayalakshmi Srinivasan, and Kailash Gopalakrishnan.In Advances in Neural Information Processing Systems. Single-image depth perception in the wild. Weifeng Chen, Zhao Fu, Dawei Yang, and Jia Deng.We perform extensive quantitative evaluation to validate our system and compare its new components against the current state-of-the-art. Altogether, the processing takes just a few seconds on a mobile device, and the result can be instantly viewed and shared. 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. 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. The resulting depth is lifted to a layered depth image, and new geometry is synthesized in parallax regions. 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 method starts by estimating depth from the 2D input image using a new monocular depth estimation network that is optimized for mobile devices. Our 3D photos are captured in a single shot and processed directly on a mobile device. We present an end-to-end system for creating and viewing 3D photos, and the algorithmic and design choices therein. 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. 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 photography is a new medium that allows viewers to more fully experience a captured moment.