mlsanityData to 7 Oct 2026

Time-Efficient Light-Field Acquisition Using Coded Aperture and Events

arXiv 2403.07244 ↗First posted 12 Mar 2024cs.CV eess.IVcited by 9

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Abstract (arXiv)

We propose a computational imaging method for time-efficient light-field acquisition that combines a coded aperture with an event-based camera. Different from the conventional coded-aperture imaging method, our method applies a sequence of coding patterns during a single exposure for an image frame. The parallax information, which is related to the differences in coding patterns, is recorded as events. The image frame and events, all of which are measured in a single exposure, are jointly used to computationally reconstruct a light field. We also designed an algorithm pipeline for our method that is end-to-end trainable on the basis of deep optics and compatible with real camera hardware. We experimentally showed that our method can achieve more accurate reconstruction than several other imaging methods with a single exposure. We also developed a hardware prototype with the potential to complete the measurement on the camera within 22 msec and demonstrated that light fields from real 3-D scenes can be obtained with convincing visual quality. Our software and supplementary video are available from our project website.

Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). Builds on 23 of its 60 references that are in the map. First posted on arXiv 12 Mar 2024.

Builds on

23 of 60 references.

References · 23

  1. 2020pixelNeRF: Neural Radiance Fields from One or Few Imagescited by 1,574
  2. 2019Event-based Vision: A Surveycited by 1,010
  3. 2020pi-GAN: Periodic Implicit Generative Adversarial Networks for 3D-Aware Image Synthesiscited by 708
  4. 2019Local Light Field Fusion: Practical View Synthesis with Prescriptive Sampling Guidelinescited by 672
  5. 2023Generative Novel View Synthesis with 3D-Aware Diffusion Modelscited by 273
  6. 2020Single-View View Synthesis with Multiplane Imagescited by 263
  7. 2020GRF: Learning a General Radiance Field for 3D Representation and Renderingcited by 183
  8. 2022SinNeRF: Training Neural Radiance Fields on Complex Scenes from a Single Imagecited by 165
  9. 2016Learning-Based View Synthesis for Light Field Camerascited by 145
  10. 2021MINE: Towards Continuous Depth MPI with NeRF for Novel View Synthesiscited by 133
  11. 20193D Ken Burns Effect from a Single Imagecited by 128
  12. 2020Event-based Stereo Visual Odometrycited by 105
11 more
  1. 2022EventNeRF: Neural Radiance Fields from a Single Colour Event Cameracited by 92
  2. 2018Semi-Dense 3D Reconstruction with a Stereo Event Cameracited by 67
  3. 2018EPINET: A Fully-Convolutional Neural Network Using Epipolar Geometry for Depth from Light Field Imagescited by 46
  4. 2023Deformable Neural Radiance Fields using RGB and Event Camerascited by 31
  5. 2016A 4D Light-Field Dataset and CNN Architectures for Material Recognitioncited by 26
  6. 2016DeepBinaryMask: Learning a Binary Mask for Video Compressive Sensingcited by 20
  7. 2021Time-Multiplexed Coded Aperture Imaging: Learned Coded Aperture and Pixel Exposures for Compressive Imaging Systemscited by 15
  8. 2018A Unified Learning Based Framework for Light Field Reconstruction from Coded Projectionscited by 7
  9. 2021Edge-aware Bidirectional Diffusion for Dense Depth Estimation from Light Fieldscited by 5
  10. 2022Acquiring a Dynamic Light Field through a Single-Shot Coded Imagecited by 4
  11. 2018Fast and Accurate Reconstruction of Compressed Color Light Fieldcited by 3

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 2; 2025: 4; 2026: 3.

9 papers.