mlsanityData to 14 Oct 2026

MIPI 2022 Challenge on RGB+ToF Depth Completion: Dataset and Report

arXiv 2209.07057 ↗First posted 15 Sep 2022cs.CVcited by 7

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Abstract (arXiv)

Developing and integrating advanced image sensors with novel algorithms in camera systems is prevalent with the increasing demand for computational photography and imaging on mobile platforms. However, the lack of high-quality data for research and the rare opportunity for in-depth exchange of views from industry and academia constrain the development of mobile intelligent photography and imaging (MIPI). To bridge the gap, we introduce the first MIPI challenge including five tracks focusing on novel image sensors and imaging algorithms. In this paper, RGB+ToF Depth Completion, one of the five tracks, working on the fusion of RGB sensor and ToF sensor (with spot illumination) is introduced. The participants were provided with a new dataset called TetrasRGBD, which contains 18k pairs of high-quality synthetic RGB+Depth training data and 2.3k pairs of testing data from mixed sources. All the data are collected in an indoor scenario. We require that the running time of all methods should be real-time on desktop GPUs. The final results are evaluated using objective metrics and Mean Opinion Score (MOS) subjectively. A detailed description of all models developed in this challenge is provided in this paper. More details of this challenge and the link to the dataset can be found at https://github.com/mipi-challenge/MIPI2022.

Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Builds on 23 of its 37 references that are in the map. First posted on arXiv 15 Sep 2022.

Builds on

23 of 37 references.

References · 23

  1. 2017MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applicationscited by 3,845
  2. 2019Scalability in Perception for Autonomous Driving: Waymo Open Datasetcited by 2,451
  3. 2019Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-shot Cross-dataset Transfercited by 1,495
  4. 2016Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Networkcited by 1,204
  5. 2021ARKitScenes: A Diverse Real-World Dataset For 3D Indoor Scene Understanding Using Mobile RGB-D Datacited by 454
  6. 2017Sparsity Invariant CNNscited by 326
  7. 2020Non-Local Spatial Propagation Network for Depth Completioncited by 195
  8. 2021PENet: Towards Precise and Efficient Image Guided Depth Completioncited by 146
  9. 2018Self-supervised Sparse-to-Dense: Self-supervised Depth Completion from LiDAR and Monocular Cameracited by 140
  10. 2018Learning Depth with Convolutional Spatial Propagation Networkcited by 136
  11. 2019Learning Guided Convolutional Network for Depth Completioncited by 111
  12. 2018Depth Estimation via Affinity Learned with Convolutional Spatial Propagation Networkcited by 110
11 more
  1. 2019CSPN++: Learning Context and Resource Aware Convolutional Spatial Propagation Networks for Depth Completioncited by 110
  2. 2019Sparse and noisy LiDAR completion with RGB guidance and uncertaintycited by 79
  3. 2022Dynamic Spatial Propagation Network for Depth Completioncited by 71
  4. 2020Uncertainty-Aware CNNs for Depth Completion: Uncertainty from Beginning to Endcited by 55
  5. 2018Confidence Propagation through CNNs for Guided Sparse Depth Regressioncited by 52
  6. 2019Depth Coefficients for Depth Completioncited by 41
  7. 2021Learning Topology from Synthetic Data for Unsupervised Depth Completioncited by 38
  8. 2020Project to Adapt: Domain Adaptation for Depth Completion from Noisy and Sparse Sensor Datacited by 28
  9. 2021Depth Completion using Plane-Residual Representationcited by 24
  10. 2018Estimating Depth from RGB and Sparse Sensingcited by 23
  11. 2019Depth Completion via Deep Basis Fittingcited by 23

Built on by

Cited by year

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

7 papers.

  1. 2023MIPI 2023 Challenge on Nighttime Flare Removal: Methods and Resultscited by 6
  2. 2023MIPI 2023 Challenge on RGBW Remosaic: Methods and Resultscited by 5
  3. 2023MIPI 2023 Challenge on RGB+ToF Depth Completion: Methods and Resultscited by 4
  4. 2024CFPNet: Improving Lightweight ToF Depth Completion via Cross-zone Feature Propagationcited by 4
  5. 2023MIPI 2023 Challenge on RGBW Fusion: Methods and Resultscited by 3
  6. 2025DEPTHOR: Depth Enhancement from a Practical Light-Weight dToF Sensor and RGB Imagecited by 3
  7. 2025DEPTHOR++: Robust Depth Enhancement from a Real-World Lightweight dToF and RGB Guidancecited by 1