47 lines
1.4 KiB
Markdown
47 lines
1.4 KiB
Markdown
# CSE5519 Advances in Computer Vision (Topic E: 2021 and before: Deep Learning for Geometric Computer Vision)
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> [!NOTE]
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>
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> This topic is presented by Me. and will be the most detailed one for this course, perhaps.
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This topic is mainly about Depth Estimation from Monocular Images. (Boring, not even RANSAC)
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## PoseNet
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A Convolutional Network for Real-Time 6-DOF Camera Relocalization (ICCV 2015)
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[link to the paper](https://arxiv.org/pdf/1505.07427)
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Convolutional neural network (convnet) we train to estimate camera pose directly
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from a monocular image, $I$. Our network outputs a pose
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vector $p$, given by a 3D camera position $x$ and orientation
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represented by quaternion q:
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$$
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p = [x, q]
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$$
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$q$ is a quaternion, $x$ is a 3D camera position.
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## Unsupervised Learning of Depth and Ego-Motion From Video
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(CVPR 2017)
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[link to the paper](https://openaccess.thecvf.com/content_cvpr_2017/papers/Zhou_Unsupervised_Learning_of_CVPR_2017_paper.pdf)
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## GeoNet
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Unsupervised Learning of Dense Depth, Optical Flow and Camera Pose (CVPR 2018)
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[link to the paper](https://openaccess.thecvf.com/content_cvpr_2018/papers/Yin_GeoNet_Unsupervised_Learning_CVPR_2018_paper.pdf)
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[link to the repository](https://github.com/yzcjtr/GeoNet)
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### Rigid structure constructor
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### Non-rigid motion localizer
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### Geometric consistency enforcement
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