Self-Supervised Monocular Depth Hints

Watson, Jamie, Firman, Michael, Brostow, Gabriel, Turmukhambetov, Daniyar·2019·2019 IEEE/CVF International Conference on Computer Vision (ICCV)
DOI 10.1109/iccv.2019.00225

Cited by (273)

Items 201–273 of 273

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  2. TRICKY 2025 Challenge on Monocular Depth from Images of Specular and Transparent Surfaces
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  3. Enabling monocular depth perception at the very edge
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  4. Detaching and Boosting: Dual Engine for Scale-Invariant Self-Supervised Monocular Depth Estimation
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  5. RGB-Depth Structure Similarity for Self-supervised Monocular Depth Estimation
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  6. Dual-attention-based semantic-aware self-supervised monocular depth estimation
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  7. Lightweight Self-Supervised Monocular Depth Estimation Based on Multi-Scale Hybrid Attention
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  8. Enhancing Sustainable Intelligent Transportation Systems Through Lightweight Monocular Depth Estimation Based on Volume Density
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  9. Self-Supervised Monocular Depth Estimation Leveraging Heterogeneous Network Dynamic Distillation and Cross-Channel-Scale Attention
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  10. Distortion-Aware Depth Self-Updating for Self-Supervised Fisheye Monocular Depth Estimation
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  11. US$$^3$$Net: Ultralightweight Self-Supervised Stereo Matching Network using Depth-Aware Geometric Soft Occlusion
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  12. A Synopsis of Monocular Depth Estimation
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  13. Depth estimation using an improved stereo network
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  14. Depth Estimation using DNN Architecture and Vision-Based Transformers
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  15. GlobalDepth: Global-Aware Attention Model for Unsupervised Monocular Depth Estimation
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  16. Distilling Stereo Networks for Performant and Efficient Leaner Networks
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  17. Illumination Insensitive Monocular Depth Estimation Based on Scene Object Attention and Depth Map Fusion
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  18. Stereo-Matching Knowledge Distilled Monocular Depth Estimation Filtered by Multiple Disparity Consistency
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  19. Exploring the vulnerability of self-supervised monocular depth estimation models
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  20. 基于颜色校正和深度信息去雾的水下感知系统
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  21. Monocular Depth Estimation Algorithm for Rainy Scenes
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  22. Pose Networks Unveiled: Bridging the Gap for Monocular Depth Perception
    Yazan Dayoub, Andrey V. Savchenko, Ilya Makarov · 2024 · IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)
  23. Latent Object Embedding for Self-Supervised Monocular Depth Estimation
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  24. SwiftDepth++: An Efficient and Lightweight Model for Accurate Depth Estimation
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  25. Attention-Based Background/Foreground Monocular Depth Prediction Model Using Image Segmentation
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  26. Distilled Semantics for Comprehensive Scene Understanding from Videos
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  27. Radar-Camera Pixel Depth Association for Depth Completion
    Long, Yunfei, Daniel Morris, Xiaoming Liu, Marcos P. Gerardo Castro, Punarjay Chakravarty, Narayanan, Praveen · 2021 · arXiv (Cornell University)
  28. Joint Estimation of Depth and Pose with IMU-assisted Photometric Loss
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  29. Towards Loss Balance and Consistent Model in Self-supervised Monocular Depth Estimation
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  30. Towards Continual, Online, Unsupervised Depth.
    Muhammad Umar Karim Khan · 2021 · arXiv (Cornell University)
  31. Aprendizagem profunda aplicada a estimação monocular de profundidade: uma abordagem baseada em atenção e complementação
    Raul de Queiroz Mendes · 2021 · Digital Library of Theses and Dissertations (Universidade de São Paulo)
  32. Human Head Pose Estimation Through Temporal Enhanced and Accurate Self-Supervised Depth Prediction
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  33. Single Input Stereo HDR Imaging using Deep Learning
    Arya S Potti, Gayathri Suresh, A S Gayathri, Anjitha Raju, Anoop K. Johnson · 2021 · International Conference on Advancements in Electrical, Electronics, Communication, Computing and Automation (ICAECA)
  34. Does Depth Estimation Help Object Detection?
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  35. An unsupervised monocular image depth prediction algorithm using Fourier domain analysis
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  36. Multilevel feature fusion and edge optimization network for self-supervised monocular depth estimation
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  37. Monocular Depth Estimation of Indoor Environments Using Enhanced Rgb-D Dataset
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  38. Semi-Supervised Depth Estimation by Multi-Task Learning
    Qingshun Fu, Xuan Dong · 2022 · Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition
  39. Geometric-Aware Calibration Mechanism for Self-Supervised Depth Estimation
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  40. Detail-Preserving Self-Supervised Monocular Depth with Self-Supervised Structural Sharpening
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  41. Integrating Semantic Segmentation Model for Self-Supervised Scene Flow Estimation Via Cross Task
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  42. UWDepth:Underwater image Depth estimation
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  43. Night vision self-supervised Reflectance-Aware Depth Estimation based on reflectance
    Yu Yao, Fangling Pu, Hongjia Chen, Rui Tang, Jinwen Li, Xin Xu · 2023 · Journal of Visual Communication and Image Representation
  44. MRA-Depth: Multi-Resolution Attention based Monocular Depth Estimation
    Jing A. Wen, Lukuan Niu · 2023 · International Conference on Robotics and Computer Vision (ICRCV)
  45. Addressing the Scale Shrinkage Problem in Learning-based Binocular Depth Estimation
    Gang Guo, Yixu Song, Fuchun Sun · 2023 · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
  46. Unsupervised Learning for Depth Estimation in Unstructured Environments
    Pian Qi, Fabio Giampaolo, Edoardo Prezioso, Francesco Piccialli · 2023 · IEEE International Conference on Big Data (BigData)
  47. Optical-Flow-Aided Self-Supervised Single View Depth Estimation from Monocular Videos
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  48. Integrating Semantic Segmentation Model for Self-Supervised Scene Flow Estimation via Cross Task Distillation
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  49. Enhanced blur‐robust monocular depth estimation via self‐supervised learning
    Chi‐Hun Sung, Seong‐Yeol Kim, Ho‐Ju Shin, Se‐Ho Lee, Seung‐Wook Kim · 2024 · Electronics Letters
  50. MaskingDepth: Masked Consistency Regularization for Semi-Supervised Monocular Depth Estimation
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  51. Misleading Supervision Removal Mechanism for self-supervised monocular depth estimation
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  52. SPIdepth: A Novel Approach to Enhancing Monocular Depth Estimation with Strengthened Pose Networks
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  53. Optical Lens Attack on Deep Learning Based Monocular Depth Estimation
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  54. Let the Monocular Depth Estimation Model See Further
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  55. CT-Mono: Leveraging CNNs and Transformers for Self-Supervised Depth Estimation in Single-View Scenarios
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  56. PanoMambaDepth: Self-supervised Omnidirectional Monocular Depth Estimation With Self-distilled Panoramic Mamba Network
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  57. Self-supervised Monocular Depth Estimation for Dynamic Objects with Ground Propagation
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  58. Enhanced Modeling for Self-Supervised Monocular Depth Estimation
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  59. Robust Adversarial Patch Via Multi-View Optimization for Monocular Depth Estimation
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  60. Breaking Monocular Depth Estimation with DepthHack: A Black-box 3D Physical Adversarial Attack for Autonomous Driving
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  61. Self‐Supervised Monocular Depth Estimation: A Review of Paradigms, Evaluation Protocols, and Technical Advances
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  62. 3DGS-Depth: Occlusion-aware Self-supervised Monocular Depth Estimation via 3D Gaussian Splatting
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  63. 3D scene reconstruction from images
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  64. Security and Robustness of Autonomous Driving Systems Against Physical Adversarial Attack
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  65. Knowledge Distillation with Context-Aware Refinement for Self-Supervised Depth Estimation in Transparent Environments
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  66. AerialNet: Monocular Depth Estimation Architecture for UAV Aerial Images Using ViT & GraphSAGE
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  67. Self-Supervised Monocular Depth Estimation With Multimodal Fusion and Pose Enhancement
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  68. Confidence Through Parallel Attention for Depth and Uncertainty Estimation in Dynamic Environments
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  69. Adversarial Patches in 3D: A Stealth Threat to Monocular Depth Estimation
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  70. Vigdepth: self-supervised monocular depth estimation based on vision GNN and local graph reasoning
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  71. Towards Robust Driving Perception: A Flexible Scale-Driven Family for Self-Supervised Monocular Depth Estimation
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  72. Geometric Distillation from Rectified Stereo: Leveraging Epipolar Cues for Monocular Depth
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  73. JEPADepth: Self-Supervised Monocular Depth Estimation via Joint-Embedding Predictive Architectures
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