Title | Authors | Venue/Publisher | Year | Resources |
---|---|---|---|---|
Eliminating the Blind Spot: Adapting 3D Object Detection and Monocular Depth Estimation to |
Grégoire Payen de La Garanderie et al. | ECCV | 2018 | [PDF] [CODE] |
360D: A dataset and baseline for dense depth estimation from 360 images | Antonis Karakottas et al. | ECCV | 2018 | [PDF] |
HoHoNet: 360 Indoor Holistic Understanding with Latent Horizontal Features | Cheng Sun et al. | CVPR | 2020 | [PDF] [CODE] |
Deep Depth Estimation on |
Brandon Yushan Feng et al. | 3DV | 2020 | [PDF] |
Geometric Structure Based and Regularized Depth Estimation From 360 Indoor Imagery | Lei Jin et al. | CVPR | 2020 | [PDF] |
Foreground-aware dense depth estimation for 360 images | Qi Eng et al. | WSCG | 2020 | [PDF] |
BiFuse: Monocular 360 Depth Estimation via Bi-Projection Fusion | Fu-En Wang et al. | CVPR | 2020 | [PDF] [CODE] |
UniFuse: Unidirectional Fusion for 360 Panorama Depth Estimation | Hualie Jiang et al. | CVPR | 2021 | [PDF] [CODE] |
Deep Learning-based High-precision Depth Map Estimation from Missing Viewpoints for 360 Degree Digital Holography | Hakdong Kim et al. | MDPI | 2021 | [PDF] |
Depth Estimation from a Single Omnidirectional Image using Domain Adaptation | Yihong Wu et al. | ACM | 2021 | [PDF] |
Pano3D: A Holistic Benchmark and a Solid Baseline for |
Georgios Albanis et al. | CVPR | 2021 | [PDF] [CODE] |
SliceNet: deep dense depth estimation from a single indoor panorama using a slice-based representation | Giovanni Pintore et al. | CVPR | 2021 | [PDF] [CODE] |
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] [CODE] |
Depth360: Monocular Depth Estimation using Learnable Axisymmetric Camera Model for Spherical Camera Image | Noriaki Hirose et al. | IROS | 2022 | [PDF] |
ACDNet: Adaptively Combined Dilated Convolution for Monocular Panorama Depth Estimation | Chuanqing Zhuang et al. | AAAI | 2022 | [PDF] [CODE] |
Rethinking Supervised Depth Estimation for |
Lu He et al. | CVF | 2022 | [PDF] |
HiMODE: A Hybrid Monocular Omnidirectional Depth Estimation Model | Masum Shah Junayed et al. | CVF | 2022 | [PDF] [CODE] |
Neural Contourlet Network for Monocular |
Zhijie Shen et al. | IEEE TCSVT | 2022 | [PDF] [CODE] |
GLPanoDepth: Global-to-Local Panoramic Depth Estimation | Jiayang Bai et al. | IEEE TIP | 2022 | [PDF] [CODE] |
360 Depth Estimation in the Wild -- the Depth360 Dataset and the SegFuse Network | Qi Feng et al. | CVPR | 2022 | [PDF] [CODE] |
BiFuse++: Self-supervised and Efficient Bi-projection Fusion for |
Fu-En Wang et al. | 3D Research | 2022 | [PDF] [CODE] |
PanoFormer: Panorama Transformer for Indoor |
Zhijie Shen et al. | CVPR | 2022 | [PDF] [CODE] |
OmniFusion: 360 Monocular Depth Estimation via Geometry Aware Fusion | Yuyan Li et al. | CVPR | 2022 | [PDF] [CODE] |
SphereDepth: Panorama Depth Estimation from Spherical Domain | Qingsong Yan et al. | CVPR | 2022 | [PDF] [CODE] |
360MonoDepth: High-Resolution |
Manuel Rey-Area et al. | CVPR | 2022 | [PDF] [CODE] |
Distortion-Aware Self-Supervised |
Yuya Hasegawa et al. | IEEE | 2022 | [PDF] |
PanoFormer: Panorama Transformer for Indoor |
Zhijie Shen et al. | ECCV | 2022 | [PDF] [CODE] |
Learning high-quality depth map from |
Chao Xu et al. | Springer | 2022 | [LINK] |
Adversarial Mixture Density Network and Uncertainty-based Joint Learning for |
Ilwi Yun et al. | IEEE | 2023 | [LINK] |
High-Resolution Depth Estimation for 360-degree Panoramas through Perspective and Panoramic Depth Images Registration | Chi-Han Peng et al. | WACV | 2023 | [PDF] |
|
Meng Li et al. | CVPR | 2023 | [PDF] [CODE] |
ZoeDepth: Zero-shot Transfer by Combining Relative and Metric Depth 1 | Shariq Farooq Bhat et al. | arXiv | 2023 | [PDF] [CODE] |
EGformer: Equirectangular Geometry-biased Transformer for 360 Depth Estimation | Ilwi Yun et al. | ICCV | 2023 | [PDF] [CODE] |
FreDSNet: Joint Monocular Depth and Semantic Segmentation with Fast Fourier Convolutions | Bruno Berenguel-Baeta et al. | ICRA | 2023 | [PDF] [CODE] |
Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data 1 | Lihe Yang et al. | CVPR | 2024 | [PDF] [CODE] |
Title | Authors | Venue/Publisher | Year | Resources |
---|---|---|---|---|
Spherical View Synthesis for Self-Supervised 360 Depth Estimation | Nikolaos Zioulis et al. | 3DV | 2019 | [PDF] [CODE] |
|
Ren Komatsu et al. | IROS | 2020 | [PDF] [CODE] |
MODE: Multi-view Omnidirectional Depth Estimation with |
Ming Li et al. | ECCV | 2022 | [PDF] [CODE] |
Semi-Supervised 360° Depth Estimation from Multiple Fisheye Cameras with Pixel-Level Selective Loss | Jaewoo Lee et al. | ICASSP | 2022 | [PDF] [CODE] |
Dense Depth Estimation from Multiple 360-degree Images Using Virtual Depth | Seongyeop Yang et al. | Springer | 2022 | [PDF] [CODE] |