mlsanityData to 7 Oct 2026

360deg Optical Flow using Tangent Images

arXiv 2112.14331 ↗First posted 28 Dec 2021cs.CVcited by 7

Not on the map. Why?

Abstract (arXiv)

Omnidirectional 360deg images have found many promising and exciting applications in computer vision, robotics and other fields, thanks to their increasing affordability, portability and their 360deg field of view. The most common format for storing, processing and visualising 360deg images is equirectangular projection (ERP). However, the distortion introduced by the nonlinear mapping from 360deg image to ERP image is still a barrier that holds back ERP images from being used as easily as conventional perspective images. This is especially relevant when estimating 360deg optical flow, as the distortions need to be mitigated appropriately. In this paper, we propose a 360deg optical flow method based on tangent images. Our method leverages gnomonic projection to locally convert ERP images to perspective images, and uniformly samples the ERP image by projection to a cubemap and regular icosahedron vertices, to incrementally refine the estimated 360deg flow fields even in the presence of large rotations. Our experiments demonstrate the benefits of our proposed method both quantitatively and qualitatively.

Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Builds on 25 of its 52 references that are in the map. First posted on arXiv 28 Dec 2021.

Builds on

25 of 52 references.

References · 25

  1. 2020RAFT: Recurrent All-Pairs Field Transforms for Optical Flowcited by 2,385
  2. 2015FlowNet: Learning Optical Flow with Convolutional Networkscited by 1,054
  3. 2017PWC-Net: CNNs for Optical Flow Using Pyramid, Warping, and Cost Volumecited by 966
  4. 2019The Replica Dataset: A Digital Replica of Indoor Spacescited by 885
  5. 2016FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networkscited by 780
  6. 2020HoHoNet: 360 Indoor Holistic Understanding with Latent Horizontal Featurescited by 104
  7. 2018OmniDepth: Dense Depth Estimation for Indoors Spherical Panoramascited by 98
  8. 2018Models Matter, So Does Training: An Empirical Study of CNNs for Optical Flow Estimationcited by 94
  9. 2021UniFuse: Unidirectional Fusion for 360circ Panorama Depth Estimationcited by 91
  10. 2019Tangent Images for Mitigating Spherical Distortioncited by 79
  11. 2016Fast Optical Flow using Dense Inverse Searchcited by 70
  12. 2018Cube Padding for Weakly-Supervised Saliency Prediction in 360deg Videoscited by 66
13 more
  1. 2018Kernel Transformer Networks for Compact Spherical Convolutioncited by 56
  2. 2019Corners for Layout: End-to-End Layout Recovery from 360 Imagescited by 55
  3. 2019Orientation-aware Semantic Segmentation on Icosahedron Spherescited by 52
  4. 2019Spherical View Synthesis for Self-Supervised 360 Depth Estimationcited by 51
  5. 2021Capturing Omni-Range Context for Omnidirectional Segmentationcited by 49
  6. 2021LED2-Net: Monocular 360 Layout Estimation via Differentiable Depth Renderingcited by 42
  7. 2018Self-Supervised Learning of Depth and Camera Motion from 360deg Videoscited by 40
  8. 2018SpherePHD: Applying CNNs on a Spherical PolyHeDron Representation of 360 degree Imagescited by 40
  9. 2019360SD-Net: 360deg Stereo Depth Estimation with Learnable Cost Volumecited by 40
  10. 2021Learning optical flow from still imagescited by 28
  11. 2019Pano Popups: Indoor 3D Reconstruction with a Plane-Aware Networkcited by 25
  12. 2021Layout-Guided Novel View Synthesis from a Single Indoor Panoramacited by 16
  13. 2020Revisiting Optical Flow Estimation in 360 Videoscited by 12

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 2; 2023: 1; 2024: 1; 2025: 2; 2026: 1.

7 papers.