|
| | | | |
| | | |
| Stat |
Members: 3645
Articles: 2'503'724
Articles rated: 2609
24 April 2024 |
|
| | | | |
|
Article overview
| |
|
|
Learning Single Camera Depth Estimation using Dual-Pixels | | Rahul Garg
; Neal Wadhwa
; Sameer Ansari
; Jonathan T. Barron
; | | Date: |
11 Apr 2019 | | Abstract: | Deep learning techniques have enabled rapid progress in monocular depth
estimation, but their quality is limited by the ill-posed nature of the problem
and the scarcity of high quality datasets. We estimate depth from a single
camera by leveraging the dual-pixel auto-focus hardware that is increasingly
common on modern camera sensors. Classic stereo algorithms and prior
learning-based depth estimation techniques under-perform when applied on this
dual-pixel data, the former due to too-strong assumptions about RGB image
matching, and the latter due to a lack of understanding of the optics of
dual-pixel image formation. To allow learning based methods to work well on
dual-pixel imagery, we identify an inherent ambiguity in the depth estimated
from dual-pixel cues, and develop an approach to estimate depth up to this
ambiguity. Using our approach, existing monocular depth estimation techniques
can be effectively applied to dual-pixel data, and much smaller models can be
constructed that still infer high quality depth. To demonstrate this, we
capture a large dataset of in-the-wild 5-viewpoint RGB images paired with
corresponding dual-pixel data, and show how view supervision with this data can
be used to learn depth up to the unknown ambiguities. On our new task, our
model is 30% more accurate than any prior work on learning-based monocular or
stereoscopic depth estimation. | | Source: | arXiv, 1904.5822 | | Services: | Forum | Review | PDF | Favorites | |
|
|
No review found.
Did you like this article?
Note: answers to reviews or questions about the article must be posted in the forum section.
Authors are not allowed to review their own article. They can use the forum section.
browser Mozilla/5.0 AppleWebKit/537.36 (KHTML, like Gecko; compatible; ClaudeBot/1.0; +claudebot@anthropic.com)
|
| |
|
|
|
|
News, job offers and information for researchers and scientists:
| |
REGISTER