Yongsen Mao commited on
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Add VP Hough Transform Gaussian Sphere models

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README.md CHANGED
@@ -6,6 +6,8 @@ license: mit
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  PySceneKit is an open-source Python library designed for common scene processing and visualization tasks. Whether you're working with 2D or 3D scenes, PySceneKit provides a comprehensive toolkit to help you manipulate, analyze, and visualize your data with ease.
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  ## Introduction
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  Welcome to PySceneKit! This project is fueled by my passion for scene understanding, particularly in indoor environments. Frustrated by the lack of user-friendly tools for processing images and 3D indoor scenes, I often found myself rewriting code for different datasets.
 
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  PySceneKit is an open-source Python library designed for common scene processing and visualization tasks. Whether you're working with 2D or 3D scenes, PySceneKit provides a comprehensive toolkit to help you manipulate, analyze, and visualize your data with ease.
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+ GitHub: https://github.com/SamMaoYS/pyscenekit
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+
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  ## Introduction
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  Welcome to PySceneKit! This project is fueled by my passion for scene understanding, particularly in indoor environments. Frustrated by the lack of user-friendly tools for processing images and 3D indoor scenes, I often found myself rewriting code for different datasets.
dsine/LICENSE ADDED
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+ SCHEDULE 1
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+ The Software
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+ DSINE is a framework for estimating surface normals from a single image. It is based on the techniques described in the following publication:
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+
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+ • Gwangbin Bae, Andrew J. Davison. Rethinking Inductive Biases for Surface Normal Estimation. CVPR, 2024
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+ _________________________
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+
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+ Acknowledgments
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+ If you use the software, you should reference the following paper in any publication:
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+
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+ • Gwangbin Bae, Andrew J. Davison. Rethinking Inductive Biases for Surface Normal Estimation. CVPR, 2024
dsine/README.md ADDED
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+ # DSINE
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+
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+ Rethinking Inductive Biases for Surface Normal Estimation
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+
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+ Authors: Gwangbin Bae, Andrew J. Davison
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+
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+ https://github.com/baegwangbin/DSINE
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+
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+ ```bibtex
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+ @inproceedings{bae2024dsine,
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+ title = {Rethinking Inductive Biases for Surface Normal Estimation},
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+ author = {Gwangbin Bae and Andrew J. Davison},
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+ booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
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+ year = {2024}
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+ }
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+ ```
vp_houghtransform_gaussiansphere/LICENSE ADDED
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+ MIT License
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+
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+ Copyright (c) 2022 CVisioner
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+
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+ Permission is hereby granted, free of charge, to any person obtaining a copy
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+ of this software and associated documentation files (the "Software"), to deal
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+ in the Software without restriction, including without limitation the rights
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+ to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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+ copies of the Software, and to permit persons to whom the Software is
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+ furnished to do so, subject to the following conditions:
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+
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+ The above copyright notice and this permission notice shall be included in all
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+ copies or substantial portions of the Software.
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+
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+ THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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+ IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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+ FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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+ AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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+ LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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+ OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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+ SOFTWARE.
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+ lr_decay_epoch: 24
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+ max_epoch: 36
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+ name: Adam
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vp_houghtransform_gaussiansphere/README.md ADDED
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+ # VP Hough Transform Gaussian Sphere
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+
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+ Deep vanishing point detection: Geometric priors make dataset variations vanish
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+
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+ Authors: Yancong Lin, Ruben Wiersma, Silvia L. Pintea, Klaus Hildebrandt, Elmar Eisemann, Jan C. van Gemert
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+
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+ Original repo: https://github.com/yanconglin/VanishingPoint_HoughTransform_GaussianSphere
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+
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+ ```bibtex
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+ @article{lin2022vpd,
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+ title={Deep vanishing point detection: Geometric priors make dataset variations vanish},
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+ author={Lin, Yancong and Wiersma, Ruben and and Pintea, Silvia L and Hildebrandt, Klaus and Eisemann, Elmar and van Gemert, Jan C},
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+ booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
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+ year={2022}
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+ }
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+ ```
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