mlsanityData to 7 Oct 2026

iToF2dToF: A Robust and Flexible Representation for Data-Driven Time-of-Flight Imaging

arXiv 2103.07087 ↗First posted 12 Mar 2021cs.CV eess.IVcited by 11

Not on the map. Why?

Abstract (arXiv)

Indirect Time-of-Flight (iToF) cameras are a promising depth sensing technology. However, they are prone to errors caused by multi-path interference (MPI) and low signal-to-noise ratio (SNR). Traditional methods, after denoising, mitigate MPI by estimating a transient image that encodes depths. Recently, data-driven methods that jointly denoise and mitigate MPI have become state-of-the-art without using the intermediate transient representation. In this paper, we propose to revisit the transient representation. Using data-driven priors, we interpolate/extrapolate iToF frequencies and use them to estimate the transient image. Given direct ToF (dToF) sensors capture transient images, we name our method iToF2dToF. The transient representation is flexible. It can be integrated with different rule-based depth sensing algorithms that are robust to low SNR and can deal with ambiguous scenarios that arise in practice (e.g., specular MPI, optical cross-talk). We demonstrate the benefits of iToF2dToF over previous methods in real depth sensing scenarios.

Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). Builds on 16 of its 66 references that are in the map. First posted on arXiv 12 Mar 2021.

Builds on

16 of 66 references.

References · 16

  1. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
  2. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,160
  3. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
  4. 2017MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applicationscited by 3,827
  5. 2017End-to-End Learning of Geometry and Context for Deep Stereo Regressioncited by 359
  6. 2017A Survey of Model Compression and Acceleration for Deep Neural Networkscited by 298
  7. 2019Asynchronous Single-Photon 3D Imagingcited by 25
  8. 2018Tackling 3D ToF Artifacts Through Learning and the FLAT Datasetcited by 21
  9. 2019Deep End-to-End Alignment and Refinement for Time-of-Flight RGB-D Modulecited by 14
  10. 2018DeepToF: Off-the-Shelf Real-Time Correction of Multipath Interference in Time-of-Flight Imagingcited by 13
  11. 2016Recent Advances in Transient Imaging: A Computer Graphics and Vision Perspectivecited by 12
  12. 2016Learning to Remove Multipath Distortions in Time-of-Flight Range Images for a Robotic Arm Setupcited by 11
4 more
  1. 2014SRA: Fast Removal of General Multipath for ToF Sensorscited by 10
  2. 2015Bayesian Time-of-Flight for Realtime Shape, Illumination and Albedocited by 8
  3. 2018Very Power Efficient Neural Time-of-Flightcited by 8
  4. 2018Long-range depth imaging using a single-photon detector array and non-local data fusioncited by 5

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 2; 2022: 2; 2023: 1; 2024: 2; 2025: 2; 2026: 2.

11 papers.