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https://github.com/bkhanal-11/awesome-360-depth-estimation
State-of-the-art papers for depth estimation of 360 images.
https://github.com/bkhanal-11/awesome-360-depth-estimation
List: awesome-360-depth-estimation
equirectangular-panorama monocular-depth-estimation transformer
Last synced: 3 months ago
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State-of-the-art papers for depth estimation of 360 images.
- Host: GitHub
- URL: https://github.com/bkhanal-11/awesome-360-depth-estimation
- Owner: bkhanal-11
- License: gpl-3.0
- Created: 2023-02-09T04:57:16.000Z (over 1 year ago)
- Default Branch: master
- Last Pushed: 2024-02-26T12:00:29.000Z (8 months ago)
- Last Synced: 2024-05-19T15:01:36.484Z (6 months ago)
- Topics: equirectangular-panorama, monocular-depth-estimation, transformer
- Homepage:
- Size: 31.3 KB
- Stars: 28
- Watchers: 6
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- ultimate-awesome - awesome-360-depth-estimation - State-of-the-art papers for depth estimation of 360 images. (Other Lists / PowerShell Lists)
README
# Awesome 360 Depth Estimation [](https://github.com/sindresorhus/awesome)
## Papers
### Single 360 image
| Title | Authors | Venue/Publisher | Year | Resources |
| :----------------------------------------------------------- | ---------------------------- | ----- | ---- | ------------------------------------------------------------ |
| Eliminating the Blind Spot: Adapting 3D Object Detection and Monocular Depth Estimation to $360^{\circ}$ Panoramic Imagery | Grégoire Payen de La Garanderie et al. | ECCV | 2018 | [[PDF]](https://arxiv.org/pdf/1808.06253) [[CODE]](https://github.com/gdlg/panoramic-depth-estimation)|
| 360D: A dataset and baseline for dense depth estimation from 360 images | Antonis Karakottas et al. | ECCV | 2018 | [[PDF]](https://vcl3d.github.io/assets/files/360D_ECCV2018_Workshop.pdf)|
| HoHoNet: 360 Indoor Holistic Understanding with Latent Horizontal Features | Cheng Sun et al. | CVPR | 2020 | [[PDF]](https://arxiv.org/pdf/2011.11498) [[CODE]](https://github.com/sunset1995/HoHoNet)|
| Deep Depth Estimation on $360^{\circ}$ Images with a Double Quaternion Loss | Brandon Yushan Feng et al. | 3DV | 2020 | [[PDF]](https://3dvar.com/Feng2020Deep.pdf)|
| Geometric Structure Based and Regularized Depth Estimation From 360 Indoor Imagery | Lei Jin et al. | CVPR | 2020 | [[PDF]](https://openaccess.thecvf.com/content_CVPR_2020/papers/Jin_Geometric_Structure_Based_and_Regularized_Depth_Estimation_From_360_Indoor_CVPR_2020_paper.pdf)|
| Foreground-aware dense depth estimation for 360 images | Qi Eng et al. | WSCG | 2020 | [[PDF]](http://wscg.zcu.cz/wscg2020/Abstracts/F89.html) |
| BiFuse: Monocular 360 Depth Estimation via Bi-Projection Fusion | Fu-En Wang et al. | CVPR | 2020 | [[PDF]](https://openaccess.thecvf.com/content_CVPR_2020/papers/Wang_BiFuse_Monocular_360_Depth_Estimation_via_Bi-Projection_Fusion_CVPR_2020_paper.pdf) [[CODE]](https://github.com/Yeh-yu-hsuan/BiFuse) |
| UniFuse: Unidirectional Fusion for 360 Panorama Depth Estimation | Hualie Jiang et al. | CVPR | 2021 | [[PDF]](https://arxiv.org/pdf/2102.03550.pdf) [[CODE]](https://github.com/alibaba/UniFuse-Unidirectional-Fusion) |
| Deep Learning-based High-precision Depth Map Estimation from Missing Viewpoints for 360 Degree Digital Holography | Hakdong Kim et al. | MDPI | 2021 | [[PDF]](https://arxiv.org/pdf/2103.05158.pdf) |
| Depth Estimation from a Single Omnidirectional Image using Domain Adaptation | Yihong Wu et al. | ACM | 2021 | [[PDF]](http://www.3dkim.com/Eng/papers/31ICASSP.pdf) |
| Pano3D: A Holistic Benchmark and a Solid Baseline for $360^{\circ}$ Depth Estimation | Georgios Albanis et al. | CVPR | 2021 | [[PDF]](https://arxiv.org/pdf/2109.02749.pdf) [[CODE]](https://github.com/VCL3D/Pano3D)|
| SliceNet: deep dense depth estimation from a single indoor panorama using a slice-based representation | Giovanni Pintore et al. | CVPR | 2021 | [[PDF]](https://openaccess.thecvf.com/content/CVPR2021/papers/Pintore_SliceNet_Deep_Dense_Depth_Estimation_From_a_Single_Indoor_Panorama_CVPR_2021_paper.pdf) [[CODE]](https://github.com/crs4/SliceNet)|
| Improving 360◦ Monocular Depth Estimation via Non-local Dense Prediction Transformer and Joint Supervised and Self-supervised Learning | Ilwi Yun et al. | AAAI | 2022 | [[PDF]](https://arxiv.org/pdf/2109.10563.pdf) [[CODE]](https://github.com/yuniw18/Joint_360depth)|
| Depth360: Monocular Depth Estimation using Learnable Axisymmetric Camera Model for Spherical Camera Image | Noriaki Hirose et al. | IROS | 2022 | [[PDF]](https://arxiv.org/pdf/2110.10415v1.pdf)|
| ACDNet: Adaptively Combined Dilated Convolution for Monocular Panorama Depth Estimation | Chuanqing Zhuang et al. | AAAI | 2022 | [[PDF]](https://arxiv.org/pdf/2112.14440v2) [[CODE]](https://github.com/zcq15/ACDNet)|
| Rethinking Supervised Depth Estimation for $360^{\circ}$ Panoramic Imagery | Lu He et al. | CVF | 2022 | [[PDF]](https://openaccess.thecvf.com/content/CVPR2022W/OmniCV/papers/He_Rethinking_Supervised_Depth_Estimation_for_360deg_Panoramic_Imagery_CVPRW_2022_paper.pdf)|
| HiMODE: A Hybrid Monocular Omnidirectional Depth Estimation Model | Masum Shah Junayed et al. | CVF | 2022 | [[PDF]](https://arxiv.org/pdf/2204.05007v1) [[CODE]](https://github.com/himode5008/HiMODE)|
| Neural Contourlet Network for Monocular $360^{\circ}$ Depth Estimation | Zhijie Shen et al. | IEEE TCSVT | 2022 | [[PDF]](https://arxiv.org/pdf/2208.01817v1) [[CODE]](https://github.com/zhijieshen-bjtu/Neural-Contourlet-Network-for-MODE) |
| GLPanoDepth: Global-to-Local Panoramic Depth Estimation | Jiayang Bai et al. | IEEE TIP | 2022 | [[PDF]](https://arxiv.org/pdf/2202.02796v2) [[CODE]](https://github.com/LeoDarcy/GLPanoDepth) |
| 360 Depth Estimation in the Wild -- the Depth360 Dataset and the SegFuse Network | Qi Feng et al. | CVPR | 2022 | [[PDF]](https://arxiv.org/pdf/2202.08010.pdf) [[CODE]](https://github.com/HAL-lucination/segfuse) |
| BiFuse++: Self-supervised and Efficient Bi-projection Fusion for $360^{\circ}$ Depth Estimation | Fu-En Wang et al. | 3D Research | 2022 | [[PDF]](https://arxiv.org/pdf/2209.02952.pdf) [[CODE]](https://github.com/fuenwang/BiFusev2)|
| PanoFormer: Panorama Transformer for Indoor $360^{\circ}$ Depth Estimation | Zhijie Shen et al. | CVPR | 2022 | [[PDF]](https://arxiv.org/pdf/2203.09283.pdf) [[CODE]](https://github.com/zhijieshen-bjtu/PanoFormer) |
| OmniFusion: 360 Monocular Depth Estimation via Geometry Aware Fusion | Yuyan Li et al. | CVPR | 2022 | [[PDF]](https://arxiv.org/pdf/2202.01323.pdf) [[CODE]](https://github.com/yuyanli0831/OmniFusion) |
| SphereDepth: Panorama Depth Estimation from Spherical Domain | Qingsong Yan et al. | CVPR | 2022 | [[PDF]](https://arxiv.org/pdf/2208.13714v1.pdf) [[CODE]](https://github.com/Yannnnnnnnnnnn/SphereDepth) |
| 360MonoDepth: High-Resolution $360^{\circ}$ Monocular Depth Estimation | Manuel Rey-Area et al. | CVPR | 2022 | [[PDF]](https://arxiv.org/pdf/2111.15669.pdf) [[CODE]](https://github.com/manurare/360monodepth) |
| Distortion-Aware Self-Supervised $360^{\circ}$ Depth Estimation from A Single Equirectangular Projection Image | Yuya Hasegawa et al. | IEEE | 2022 | [[PDF]](https://arxiv.org/pdf/2204.01027v1.pdf) |
| PanoFormer: Panorama Transformer for Indoor $360^{\circ}$ Depth Estimation | Zhijie Shen et al. | ECCV | 2022 | [[PDF]](https://arxiv.org/pdf/2203.09283.pdf) [[CODE]](https://github.com/zhijieshen-bjtu/PanoFormer) |
| Learning high-quality depth map from $360^{\circ}$ multi-exposure imagery | Chao Xu et al. | Springer | 2022 | [[LINK]](https://link.springer.com/article/10.1007/s11042-022-13340-x) |
| Adversarial Mixture Density Network and Uncertainty-based Joint Learning for $360^{\circ}$ Monocular Depth Estimation | Ilwi Yun et al. | IEEE | 2023 | [[LINK]](https://ieeexplore.ieee.org/document/10243094) |
| High-Resolution Depth Estimation for 360-degree Panoramas through Perspective and Panoramic Depth Images Registration | Chi-Han Peng et al. | WACV | 2023 | [[PDF]](https://arxiv.org/pdf/2210.10414.pdf) |
| $\mathcal{S}^2$ Net: Accurate Panorama Depth Estimation on Spherical Surface| Meng Li et al. | CVPR | 2023 | [[PDF]](https://arxiv.org/pdf/2301.05845.pdf) [[CODE]](https://github.com/aliyun/S2net)|
| ZoeDepth: Zero-shot Transfer by Combining Relative and Metric Depth [^1] | Shariq Farooq Bhat et al. | arXiv | 2023 | [[PDF]](https://arxiv.org/pdf/2302.12288.pdf) [[CODE]](https://github.com/isl-org/ZoeDepth)|
| EGformer: Equirectangular Geometry-biased Transformer for 360 Depth Estimation | Ilwi Yun et al. | ICCV | 2023 | [[PDF]](https://arxiv.org/pdf/2304.07803.pdf) [[CODE]](https://github.com/yuniw18/EGformer)|
| FreDSNet: Joint Monocular Depth and Semantic Segmentation with Fast Fourier Convolutions | Bruno Berenguel-Baeta et al. | ICRA | 2023 | [[PDF]](https://arxiv.org/pdf/2210.01595v2) [[CODE]](https://github.com/Sbrunoberenguel/FreDSNet)|
| Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data [^1] | Lihe Yang et al. | CVPR | 2024 | [[PDF]](https://arxiv.org/pdf/2401.10891.pdf) [[CODE]](https://github.com/LiheYoung/Depth-Anything)|
### Multiple 360 images
| Title | Authors | Venue/Publisher | Year | Resources |
| :----------------------------------------------------------- | ---------------------------- | ----- | ---- | ------------------------------------------------------------ |
| Spherical View Synthesis for Self-Supervised 360 Depth Estimation | Nikolaos Zioulis et al. | 3DV | 2019 | [[PDF]](https://arxiv.org/pdf/1909.08112.pdf) [[CODE]](https://github.com/VCL3D/SphericalViewSynthesis) |
| $360^{\circ}$ Depth Estimation from Multiple Fisheye Images with Origami Crown Representation of Icosahedron | Ren Komatsu et al. | IROS | 2020 | [[PDF]](https://arxiv.org/pdf/2007.06891.pdf) [[CODE]](https://github.com/matsuren/crownconv360depth) |
| MODE: Multi-view Omnidirectional Depth Estimation with $360^{\circ}$ Cameras | Ming Li et al. | ECCV | 2022 | [[PDF]](https://link.springer.com/chapter/10.1007/978-3-031-19827-4_12) [[CODE]](https://github.com/nju-ee/MODE-2022) |
| Semi-Supervised 360° Depth Estimation from Multiple Fisheye Cameras with Pixel-Level Selective Loss | Jaewoo Lee et al. | ICASSP | 2022 | [[PDF]](https://link.springer.com/chapter/10.1007/978-3-031-19827-4_12) [[CODE]](https://github.com/nju-ee/MODE-2022) |
| Dense Depth Estimation from Multiple 360-degree Images Using Virtual Depth | Seongyeop Yang et al. | Springer | 2022 | [[PDF]](https://arxiv.org/pdf/2112.14931.pdf) [[CODE]](https://github.com/vcl-seoultech/360Depth) |
[^1]: These are general depth estimation algorithms which work well for 360 images as well.