mlsanityData to 7 Oct 2026

The Edge of Depth: Explicit Constraints between Segmentation and Depth

arXiv 2004.00171 ↗First posted 1 Apr 2020cs.CVcited by 72

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Abstract (arXiv)

In this work we study the mutual benefits of two common computer vision tasks, self-supervised depth estimation and semantic segmentation from images. For example, to help unsupervised monocular depth estimation, constraints from semantic segmentation has been explored implicitly such as sharing and transforming features. In contrast, we propose to explicitly measure the border consistency between segmentation and depth and minimize it in a greedy manner by iteratively supervising the network towards a locally optimal solution. Partially this is motivated by our observation that semantic segmentation even trained with limited ground truth (200 images of KITTI) can offer more accurate border than that of any (monocular or stereo) image-based depth estimation. Through extensive experiments, our proposed approach advances the state of the art on unsupervised monocular depth estimation in the KITTI.

Key facts. Cited by 72 papers in the map (data through 7 Oct 2026). First posted on arXiv 1 Apr 2020.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 14; 2022: 27; 2023: 11; 2024: 8; 2025: 5; 2026: 7.

72 papers.

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  1. 2022BinsFormer: Revisiting Adaptive Bins for Monocular Depth Estimationcited by 166
  2. 2022P3Depth: Monocular Depth Estimation with a Piecewise Planarity Priorcited by 106
  3. 2021Boosting Monocular Depth Estimation Models to High-Resolution via Content-Adaptive Multi-Resolution Mergingcited by 104
  4. 2021Self-Supervised Monocular Depth Estimation with Internal Feature Fusioncited by 67
  5. 2021Fine-grained Semantics-aware Representation Enhancement for Self-supervised Monocular Depth Estimationcited by 55
  6. 2021Radar-Camera Pixel Depth Association for Depth Completioncited by 49
  7. 2021Excavating the Potential Capacity of Self-Supervised Monocular Depth Estimationcited by 48
  8. 2021Depth Completion with Twin Surface Extrapolation at Occlusion Boundariescited by 41
  9. 2022RA-Depth: Resolution Adaptive Self-Supervised Monocular Depth Estimationcited by 36
  10. 2022BiFuse++: Self-supervised and Efficient Bi-projection Fusion for 360 Depth Estimationcited by 35
  11. 2023Tame a Wild Camera: In-the-Wild Monocular Camera Calibrationcited by 34
  12. 2022PlaneDepth: Self-supervised Depth Estimation via Orthogonal Planescited by 32
38 more
  1. 2021PLADE-Net: Towards Pixel-Level Accuracy for Self-Supervised Single-View Depth Estimation with Neural Positional Encoding and Distilled Matting Losscited by 31
  2. 2021SVDistNet: Self-Supervised Near-Field Distance Estimation on Surround View Fisheye Camerascited by 25
  3. 2022DevNet: Self-supervised Monocular Depth Learning via Density Volume Constructioncited by 22
  4. 2023SQLdepth: Generalizable Self-Supervised Fine-Structured Monocular Depth Estimationcited by 21
  5. 2022Self-Supervised Monocular Depth Estimation: Solving the Edge-Fattening Problemcited by 20
  6. 2021Learning Depth via Leveraging Semantics: Self-supervised Monocular Depth Estimation with Both Implicit and Explicit Semantic Guidancecited by 19
  7. 2022Semantic-SuPer: A Semantic-aware Surgical Perception Framework for Endoscopic Tissue Identification, Reconstruction, and Trackingcited by 19
  8. 2023EVEN: An Event-Based Framework for Monocular Depth Estimation at Adverse Night Conditionscited by 19
  9. 2022Self-distilled Feature Aggregation for Self-supervised Monocular Depth Estimationcited by 17
  10. 2022Detecting Adversarial Perturbations in Multi-Task Perceptioncited by 15
  11. 2021Towards Interpretable Deep Networks for Monocular Depth Estimationcited by 12
  12. 2021X-Distill: Improving Self-Supervised Monocular Depth via Cross-Task Distillationcited by 12
  13. 2023Temporally Consistent Online Depth Estimation Using Point-Based Fusioncited by 12
  14. 2023Delving into Crispness: Guided Label Refinement for Crisp Edge Detectioncited by 10
  15. 2021THE Benchmark: Transferable Representation Learning for Monocular Height Estimationcited by 8
  16. 2022Mind The Edge: Refining Depth Edges in Sparsely-Supervised Monocular Depth Estimationcited by 8
  17. 2023Two-in-One Depth: Bridging the Gap Between Monocular and Binocular Self-supervised Depth Estimationcited by 8
  18. 2023Joint Depth Prediction and Semantic Segmentation with Multi-View SAMcited by 8
  19. 2024SPIdepth: Strengthened Pose Information for Self-supervised Monocular Depth Estimationcited by 8
  20. 2022Learning Occlusion-Aware Coarse-to-Fine Depth Map for Self-supervised Monocular Depth Estimationcited by 6
  21. 2025Hybrid-grained Feature Aggregation with Coarse-to-fine Language Guidance for Self-supervised Monocular Depth Estimationcited by 6
  22. 2022Layered Depth Refinement with Mask Guidancecited by 5
  23. 2022UAMD-Net: A Unified Adaptive Multimodal Neural Network for Dense Depth Completioncited by 4
  24. 2023Transformer-based Multimodal Change Detection with Multitask Consistency Constraintscited by 4
  25. 2024MambaDepth: Enhancing Long-range Dependency for Self-Supervised Fine-Structured Monocular Depth Estimationcited by 4
  26. 2024RePLAy: Remove Projective LiDAR Depthmap Artifacts via Exploiting Epipolar Geometrycited by 4
  27. 2024Improving Domain Generalization in Self-supervised Monocular Depth Estimation via Stabilized Adversarial Trainingcited by 4
  28. 2025Towards Reliable Identification of Diffusion-based Image Manipulationscited by 4
  29. 2025DGFusion: Depth-Guided Sensor Fusion for Robust Semantic Perceptioncited by 4
  30. 2022Disentangled Latent Transformer for Interpretable Monocular Height Estimationcited by 3
  31. 2022Frequency-Aware Self-Supervised Monocular Depth Estimationcited by 3
  32. 2024GAM-Depth: Self-Supervised Indoor Depth Estimation Leveraging a Gradient-Aware Mask and Semantic Constraintscited by 3
  33. 2025Distribution-Specific Learning for Joint Salient and Camouflaged Object Detectioncited by 3
  34. 2021Improving Online Performance Prediction for Semantic Segmentationcited by 2
  35. 2022How Much Depth Information can Radar Contribute to a Depth Estimation Model?cited by 2
  36. 2022Zero Pixel Directional Boundary by Vector Transformcited by 2
  37. 2022DepthGAN: GAN-based Depth Generation of Indoor Scenes from Semantic Layoutscited by 2
  38. 2022Positional Information is All You Need: A Novel Pipeline for Self-Supervised SVDE from Videoscited by 2

50 most cited of 72 All 72 (JSON)