mlsanityData to 7 Oct 2026

Event-Based Dense Reconstruction Pipeline

arXiv 2203.12270 ↗First posted 23 Mar 2022cs.CVcited by 10

Not on the map. Why?

Abstract (arXiv)

Event cameras are a new type of sensors that are different from traditional cameras. Each pixel is triggered asynchronously by event. The trigger event is the change of the brightness irradiated on the pixel. If the increment or decrement of brightness is higher than a certain threshold, an event is output. Compared with traditional cameras, event cameras have the advantages of high dynamic range and no motion blur. Since events are caused by the apparent motion of intensity edges, the majority of 3D reconstructed maps consist only of scene edges, i.e., semi-dense maps, which is not enough for some applications. In this paper, we propose a pipeline to realize event-based dense reconstruction. First, deep learning is used to reconstruct intensity images from events. And then, structure from motion (SfM) is used to estimate camera intrinsic, extrinsic and sparse point cloud. Finally, multi-view stereo (MVS) is used to complete dense reconstruction.

Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). Builds on 8 of its 32 references that are in the map. First posted on arXiv 23 Mar 2022.

Builds on

8 of 32 references.

References · 8

  1. 2019High Speed and High Dynamic Range Video with an Event Cameracited by 344
  2. 2018A Unifying Contrast Maximization Framework for Event Cameras, with Applications to Motion, Depth, and Optical Flow Estimationcited by 178
  3. 2020Back to Event Basics: Self-Supervised Learning of Image Reconstruction for Event Cameras via Photometric Constancycited by 125
  4. 2018Event-based High Dynamic Range Image and Very High Frame Rate Video Generation using Conditional Generative Adversarial Networkscited by 97
  5. 2021Combining Events and Frames using Recurrent Asynchronous Multimodal Networks for Monocular Depth Predictioncited by 88
  6. 2020Learning Monocular Dense Depth from Eventscited by 84
  7. 2018Semi-Dense 3D Reconstruction with a Stereo Event Cameracited by 67
  8. 2021Research on Event Accumulator Settings for Event-Based SLAMcited by 5

Built on by

Cited by year

Citing papers per year: 2022: 2; 2023: 3; 2024: 1; 2025: 4.

10 papers.

  1. 2022EventNeRF: Neural Radiance Fields from a Single Colour Event Cameracited by 92
  2. 2023Deep Learning for Event-based Vision: A Comprehensive Survey and Benchmarkscited by 90
  3. 2023Robust e-NeRF: NeRF from Sparse & Noisy Events under Non-Uniform Motioncited by 44
  4. 2024Event3DGS: Event-Based 3D Gaussian Splatting for High-Speed Robot Egomotioncited by 22
  5. 2023Dense Voxel 3D Reconstruction Using a Monocular Event Cameracited by 7
  6. 2025Towards End-to-End Neuromorphic Event-based 3D Object Reconstruction Without Physical Priorscited by 7
  7. 2025A Survey of 3D Reconstruction with Event Camerascited by 4
  8. 2025A Survey on Event-driven 3D Reconstruction: Development under Different Categoriescited by 2
  9. 2022A Preliminary Research on Space Situational Awareness Based on Event Camerascited by 1
  10. 2025SaENeRF: Suppressing Artifacts in Event-based Neural Radiance Fieldscited by 1