mlsanityData to 14 Oct 2026

SharinGAN: Combining Synthetic and Real Data for Unsupervised Geometry Estimation

arXiv 2006.04026 ↗First posted 7 Jun 2020cs.CVcited by 25

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Abstract (arXiv)

We propose a novel method for combining synthetic and real images when training networks to determine geometric information from a single image. We suggest a method for mapping both image types into a single, shared domain. This is connected to a primary network for end-to-end training. Ideally, this results in images from two domains that present shared information to the primary network. Our experiments demonstrate significant improvements over the state-of-the-art in two important domains, surface normal estimation of human faces and monocular depth estimation for outdoor scenes, both in an unsupervised setting.

Key facts. Cited by 25 papers in the map (data through 14 Oct 2026). First posted on arXiv 7 Jun 2020.

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Citing papers per year: 2021: 7; 2022: 8; 2023: 5; 2024: 3; 2025: 2.

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  1. 2022Multi-Frame Self-Supervised Depth with Transformerscited by 64
  2. 2022Learning Optical Flow, Depth, and Scene Flow without Real-World Labelscited by 31
  3. 2021Human-Aided Saliency Maps Improve Generalization of Deep Learningcited by 27
  4. 2021Monocular Depth Estimation through Virtual-world Supervision and Real-world SfM Self-Supervisioncited by 24
  5. 2023DualRefine: Self-Supervised Depth and Pose Estimation Through Iterative Epipolar Sampling and Refinement Toward Equilibriumcited by 16
  6. 2024PatchRefiner: Leveraging Synthetic Data for Real-Domain High-Resolution Monocular Metric Depth Estimationcited by 16
  7. 2021Self-Supervised Learning of Domain Invariant Features for Depth Estimationcited by 9
  8. 2022Learning Feature Decomposition for Domain Adaptive Monocular Depth Estimationcited by 9
  9. 2022Towards Scale Consistent Monocular Visual Odometry by Learning from the Virtual Worldcited by 8
  10. 2022Mind The Edge: Refining Depth Edges in Sparsely-Supervised Monocular Depth Estimationcited by 8
  11. 20223D-PL: Domain Adaptive Depth Estimation with 3D-aware Pseudo-Labelingcited by 6
  12. 2023Task-guided Domain Gap Reduction for Monocular Depth Prediction in Endoscopycited by 5
13 more
  1. 2025PatchRefiner V2: Fast and Lightweight Real-Domain High-Resolution Metric Depth Estimationcited by 5
  2. 2021H-GAN: the power of GANs in your Handscited by 2
  3. 2021Co-training for Deep Object Detection: Comparing Single-modal and Multi-modal Approachescited by 2
  4. 2023GenDepth: Generalizing Monocular Depth Estimation for Arbitrary Camera Parameters via Ground Plane Embeddingcited by 2
  5. 2023On the Metrics for Evaluating Monocular Depth Estimationcited by 1
  6. 2023Depth-Relative Self Attention for Monocular Depth Estimationcited by 1
  7. 2024Consistency Regularisation for Unsupervised Domain Adaptation in Monocular Depth Estimationcited by 1
  8. 2024Unsupervised Monocular Depth Estimation Based on Hierarchical Feature-Guided Diffusioncited by 1
  9. 2025An Online Adaptation Method for Robust Depth Estimation and Visual Odometry in the Open Worldcited by 1
  10. 2021Improved Detection of Face Presentation Attacks Using Image Decompositioncited by 0
  11. 2021Focusing on Shadows for Predicting Heightmaps from Single Remotely Sensed RGB Images with Deep Learningcited by 0
  12. 2022Geometric Synthesis: A Free lunch for Large-scale Palmprint Recognition Model Pretrainingcited by 0
  13. 2022MaskingDepth: Masked Consistency Regularization for Semi-supervised Monocular Depth Estimationcited by 0