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DDRNet: Depth Map Denoising and Refinement for Consumer Depth Cameras Using Cascaded CNNs
[chapter]
2018
Lecture Notes in Computer Science
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We propose a cascaded Depth Denoising and Refinement Network (DDRNet) to tackle this problem by leveraging the multi-frame fused geometry and the accompanying high quality color image through a joint training ...
Consumer depth sensors are more and more popular and come to our daily lives marked by its recent integration in the latest Iphone X. ...
Conclusion We presented the first end-to-end trainable network for depth map denoising and refinement for consumer depth cameras. ...
doi:10.1007/978-3-030-01249-6_10
fatcat:ru4ijo7novhj7gfkep5r326s4a
Edge-guided single facial depth map super-resolution using CNN
2021
IET Image Processing
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A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
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In recent years, consumer depth cameras have been widely used in digital entertainment and human-machine interaction due to the advantages of real-time performance and low cost. ...
In this work, the authors propose an edge-guided convolutional neural network for single facial depth map super-resolution. ...
Acknowledgments This work was supported by the National Key R&D Program of China under Grant No. 2019YFC1521103, the Natural Science Foundation of China, grant nos. 61572078, 61772050 and U19B2039. ...
doi:10.1049/iet-ipr.2019.1623
fatcat:mspahvcimnbwre6j7lmpidttdu