mlsanityData to 7 Oct 2026

Estimating Image Depth in the Comics Domain

arXiv 2110.03575 ↗First posted 7 Oct 2021cs.CVcited by 8

Not on the map. Why?

Abstract (arXiv)

Estimating the depth of comics images is challenging as such images a) are monocular; b) lack ground-truth depth annotations; c) differ across different artistic styles; d) are sparse and noisy. We thus, use an off-the-shelf unsupervised image to image translation method to translate the comics images to natural ones and then use an attention-guided monocular depth estimator to predict their depth. This lets us leverage the depth annotations of existing natural images to train the depth estimator. Furthermore, our model learns to distinguish between text and images in the comics panels to reduce text-based artefacts in the depth estimates. Our method consistently outperforms the existing state-ofthe-art approaches across all metrics on both the DCM and eBDtheque images. Finally, we introduce a dataset to evaluate depth prediction on comics. Our project website can be accessed at https://github.com/IVRL/ComicsDepth.

Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 28 of its 50 references that are in the map. First posted on arXiv 7 Oct 2021.

Builds on

28 of 50 references.

References · 28

  1. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
  2. 2014Conditional Generative Adversarial Netscited by 2,152
  3. 2019Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-shot Cross-dataset Transfercited by 1,484
  4. 2015A Large Dataset to Train Convolutional Networks for Disparity, Optical Flow, and Scene Flow Estimationcited by 878
  5. 2016Unsupervised Monocular Depth Estimation with Left-Right Consistencycited by 819
  6. 2018Multimodal Unsupervised Image-to-Image Translationcited by 795
  7. 2014Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognitioncited by 719
  8. 2017Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networkscited by 707
  9. 2018Pyramid Stereo Matching Networkcited by 486
  10. 2016Deeper Depth Prediction with Fully Convolutional Residual Networkscited by 402
  11. 2018Diverse Image-to-Image Translation via Disentangled Representationscited by 296
  12. 2020Consistent Video Depth Estimationcited by 220
16 more
  1. 2020Robust Consistent Video Depth Estimationcited by 188
  2. 2020HITNet: Hierarchical Iterative Tile Refinement Network for Real-time Stereo Matchingcited by 120
  3. 2020Self-supervised Monocular Trained Depth Estimation using Self-attention and Discrete Disparity Volumecited by 116
  4. 2017Semi-Supervised Deep Learning for Monocular Depth Map Predictioncited by 109
  5. 2018Real-time self-adaptive deep stereocited by 80
  6. 2019Web Stereo Video Supervision for Depth Prediction from Dynamic Scenescited by 73
  7. 2018T2Net: Synthetic-to-Realistic Translation for Solving Single-Image Depth Estimation Taskscited by 70
  8. 2018Learning Monocular Depth by Distilling Cross-domain Stereo Networkscited by 64
  9. 2019Geometry-Aware Symmetric Domain Adaptation for Monocular Depth Estimationcited by 61
  10. 2018AdaDepth: Unsupervised Content Congruent Adaptation for Depth Estimationcited by 54
  11. 2017Unsupervised Learning of Geometry with Edge-aware Depth-Normal Consistencycited by 40
  12. 2019Towards Instance-level Image-to-Image Translationcited by 36
  13. 2021Single Image Depth Estimation: An Overviewcited by 35
  14. 2020Bi3D: Stereo Depth Estimation via Binary Classificationscited by 34
  15. 2019Unsupervised Domain Adaptation for Depth Prediction from Imagescited by 29
  16. 2018Unsupervised learning for cross-domain medical image synthesis using deformation invariant cycle consistency networkscited by 10

Built on by

Cited by year

Citing papers per year: 2023: 4; 2024: 4.

8 papers.

  1. 2023DARE-GRAM : Unsupervised Domain Adaptation Regression by Aligning Inverse Gram Matricescited by 28
  2. 2024Tails Tell Tales: Chapter-Wide Manga Transcriptions with Character Namescited by 10
  3. 2024One missing piece in Vision and Language: A Survey on Comics Understandingcited by 8
  4. 2023Dense Multitask Learning to Reconfigure Comicscited by 1
  5. 2024Unlocking Comics: The AI4VA Dataset for Visual Understandingcited by 1
  6. 2023MaskSearch: Querying Image Masks at Scalecited by 0
  7. 2023Instance-guided Cartoon Editing with a Large-scale Datasetcited by 0
  8. 2024Scene Depth Estimation from Traditional Oriental Landscape Paintingscited by 0