Deep Flow Rendering: View Synthesis via Layer‐aware Reflection Flow
Novel view synthesis (NVS) generates images from unseen viewpoints based on a set of input images. It is a challenge because of inaccurate lighting optimization and geometry inference. Although current neural rendering methods have made significant progress, they still struggle to reconstruct global...
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| Veröffentlicht in: | Computer graphics forum Jg. 41; H. 4; S. 139 - 148 |
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| Format: | Journal Article |
| Sprache: | Englisch |
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Blackwell Publishing Ltd
01.07.2022
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| ISSN: | 0167-7055, 1467-8659 |
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| Abstract | Novel view synthesis (NVS) generates images from unseen viewpoints based on a set of input images. It is a challenge because of inaccurate lighting optimization and geometry inference. Although current neural rendering methods have made significant progress, they still struggle to reconstruct global illumination effects like reflections and exhibit ambiguous blurs in highly view‐dependent areas. This work addresses high‐quality view synthesis to emphasize reflection on non‐concave surfaces. We propose Deep Flow Rendering that optimizes direct and indirect lighting separately, leveraging texture mapping, appearance flow, and neural rendering. A learnable texture is used to predict view‐independent features, meanwhile enabling efficient reflection extraction. To accurately fit view‐dependent effects, we adopt a constrained neural flow to transfer image‐space features from nearby views to the target view in an edge‐preserving manner. Then we further implement a fusing renderer that utilizes the predictions of both layers to form the output image. The experiments demonstrate that our method outperforms the state‐of‐the‐art methods at synthesizing various scenes with challenging reflection effects. |
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| AbstractList | Novel view synthesis (NVS) generates images from unseen viewpoints based on a set of input images. It is a challenge because of inaccurate lighting optimization and geometry inference. Although current neural rendering methods have made significant progress, they still struggle to reconstruct global illumination effects like reflections and exhibit ambiguous blurs in highly view‐dependent areas. This work addresses high‐quality view synthesis to emphasize reflection on non‐concave surfaces. We propose Deep Flow Rendering that optimizes direct and indirect lighting separately, leveraging texture mapping, appearance flow, and neural rendering. A learnable texture is used to predict view‐independent features, meanwhile enabling efficient reflection extraction. To accurately fit view‐dependent effects, we adopt a constrained neural flow to transfer image‐space features from nearby views to the target view in an edge‐preserving manner. Then we further implement a fusing renderer that utilizes the predictions of both layers to form the output image. The experiments demonstrate that our method outperforms the state‐of‐the‐art methods at synthesizing various scenes with challenging reflection effects. |
| Author | Xie, Ning Dai, Pinxuan |
| Author_xml | – sequence: 1 givenname: Pinxuan orcidid: 0000-0001-6983-3463 surname: Dai fullname: Dai, Pinxuan organization: University of Electronic Science and Technology of China – sequence: 2 givenname: Ning orcidid: 0000-0002-1509-464X surname: Xie fullname: Xie, Ning email: seanxiening@gmail.com organization: University of Electronic Science and Technology of China |
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| Cites_doi | 10.1145/1073204.1073335 10.1145/2487228.2487238 10.1109/CVPR.2011.5995693 10.1145/237170.237199 10.1109/ICCV48922.2021.01245 10.1145/2185520.2185596 10.1145/3478513.3480496 10.1007/978-3-030-58529-7_37 10.1145/882262.882281 10.1145/3450626.3459849 10.1109/TPAMI.2009.161 10.1111/1467-8659.00334 10.1109/3DV.2015.59 10.1145/3446328 10.1111/j.1467-8659.2008.01138.x 10.1145/3415255.3422884 10.1111/j.1467-8659.2010.01824.x 10.1145/2670473.2670498 10.1145/358876.358882 10.1145/3355089.3356498 10.1145/3306346.3323035 10.1109/CVPR.2015.7299195 10.1145/3130800.3130824 10.1145/15886.15902 10.1007/978-3-319-46493-0_18 10.1109/CVPR.2016.445 10.1145/566570.566612 10.1007/978-3-030-58452-8_24 10.1145/2461912.2462009 10.1007/978-3-319-46475-6_43 10.1145/383259.383309 10.1145/344779.344925 10.1109/CVPR46437.2021.00843 10.1145/3203192 10.1145/258734.258849 10.1145/3414685.3417861 |
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| Copyright | 2022 The Author(s) Computer Graphics Forum © 2022 The Eurographics Association and John Wiley & Sons Ltd. Published by John Wiley & Sons Ltd. 2022 The Eurographics Association and John Wiley & Sons Ltd. |
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| SubjectTerms | CCS Concepts Computing methodologies → Image‐based rendering Feature extraction Flow mapping Illumination Lighting Neural networks Optimization Reflection Rendering Synthesis Texture mapping |
| Title | Deep Flow Rendering: View Synthesis via Layer‐aware Reflection Flow |
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