Unsupervised Adversarial Depth Estimation Using Cycled Generative Networks

Pilzer, Andrea, Xu, Dan, Puscas, Mihai, Ricci, Elisa, Sebe, Nicu·2018·2018 International Conference on 3D Vision (3DV)

Cited by (192)

Items 101–192 of 192

  1. Unsupervised detail-preserving network for high quality monocular depth estimation
    Mingliang Zhang, Xinchen Ye, Xin Fan · 2020 · Neurocomputing
  2. Deep Learning based Monocular Depth Prediction: Datasets, Methods and Applications
    Qing Li, Jiasong Zhu, Jun Liu, Rui Cao, Qingquan Li, Sen Jia, Guoping Qiu · 2020 · arXiv (Cornell University)
  3. Unsupervised learning of depth estimation based on attention model and global pose optimization
    Renyue Dai, Yongbin Gao, Zhijun Fang, Xiaoyan Jiang, Anjie Wang, Juan Zhang, Cengsi Zhong · 2019 · Signal Processing Image Communication
  4. Encoder-Decoder Structure With the Feature Pyramid for Depth Estimation From a Single Image
    Mengxia Tang, Songnan Chen, Ruifang Dong, Jiangming Kan · 2021 · IEEE Access
  5. End-to-end learning of self-rectification and self-supervised disparity prediction for stereo vision
    Xuchong Zhang, Yongli Zhao, Hang Wang, Han Zhai, Hongbin Sun, Nanning Zheng · 2022 · Neurocomputing
  6. Single Image Depth Estimation Using Edge Extraction Network and Dark Channel Prior
    Ying Li, Cheolkon Jung, Jin Young Kim · 2021 · IEEE Access
  7. A contextual conditional random field network for monocular depth estimation
    Jun Liu, Qing Li, Rui Cao, Wenming Tang, Guoping Qiu · 2020 · Image and Vision Computing
  8. Embodiment: Self-Supervised Depth Estimation Based on Camera Models
    Jinchang Zhang, Praveen Kumar Reddy, Xue-Iuan Wong, Yiannis Aloimonos, Guoyu Lu · 2024 · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
  9. An Unsupervised Approach for Simultaneous Visual Odometry and Single Image Depth Estimation
    Yawen Lu, Guoyu Lu · 2022 · International Joint Conference on Neural Networks (IJCNN)
  10. An Unsupervised Monocular Image Depth Prediction Algorithm Based on Multiple Loss Deep Learning
    Xiaojiao Tang, Lifang Chen · 2019 · IEEE Access
  11. Self-Supervised Learning of Depth and Ego-motion with Differentiable Bundle Adjustment
    Yunxiao Shi, Jing Hai Zhu, Yi Fang, Kuo-Chin Lien, Junli Gu · 2019 · arXiv (Cornell University)
  12. Self-Supervised Stereo Matching Method Based on SRWP and PCAM for Urban Satellite Images
    Wen Chen, Hao Chen, Shuting Yang · 2022 · Remote Sensing
  13. Multi streams with dynamic balancing-based Conditional Generative Adversarial Network for paired image generation
    Mohamed Kas, Yassine Ruichek · 2022 · Knowledge-Based Systems
  14. Self-Supervised Monocular Depth Estimation Based on High-Order Spatial Interactions
    Xiuling Wang, Minglin Yu, Haixia Wang, Xiao Lu, Zhiguo Zhang · 2024 · IEEE Sensors Journal
  15. Randomly connected neural networks for self-supervised monocular depth estimation
    Samyakh Tukra, Stamatia Giannarou · 2021 · Computer Methods in Biomechanics and Biomedical Engineering Imaging & Visualization
  16. Triaxial Squeeze Attention Module and Mutual-Exclusion Loss Based Unsupervised Monocular Depth Estimation
    Jiansheng Wei, Shuguo Pan, Wang Gao, Tao Zhao · 2022 · Neural Processing Letters
  17. Semantic Information in Contrastive Learning
    Shengjiang Quan, Masahiro Hirano, Yuji Yamakawa · 2023 · IEEE/CVF International Conference on Computer Vision (ICCV)
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    Ju Hong Yoon, Min-Gyu Park, Youngbae Hwang, Kuk‐Jin Yoon · 2019 · International Conference on 3D Vision (3DV)
  19. A Real-Time Forward Collision Warning Technique Incorporating Detection and Depth Estimation Networks
    Huai-Mu Wang, Huei‐Yung Lin · 2020 · Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics
  20. Pseudo Supervised Monocular Depth Estimation with Teacher-Student Network
    Huan Liu, Junsong Yuan, Chen Wang, Jun Chen · 2021 · arXiv (Cornell University)
  21. Towards Real-Time Monocular Depth Estimation for Robotics: A Survey
    Xingshuai Dong, Matthew Garratt, Sreenatha Gopalarao Anavatti, Hussein A. Abbass · 2021 · arXiv (Cornell University)
  22. J-RR: Joint Monocular Depth Estimation and Semantic Edge Detection Exploiting Reciprocal Relations
    Deming Wu, Dongchen Zhu, Guanghui Zhang, Wenjun Shi, Xiaolin Zhang, Jiamao Li · 2022 · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
  23. LapUNet: a novel approach to monocular depth estimation using dynamic laplacian residual U-shape networks
    Yanhui Xi, Sai Li, Zhikang Xu, Feng Zhou, Juanxiu Tian · 2024 · Scientific Reports
  24. MonoLENS: Monocular Lightweight Efficient Network with Separable Convolutions for Self-Supervised Monocular Depth Estimation
    Genki Higashiuchi, Tomoyasu Shimada, Xiangbo Kong, Haimin Yan, Hiroyuki Tomiyama · 2025 · Applied Sciences
  25. Spatially variant biases considered self-supervised depth estimation based on laparoscopic videos
    Wenda Li, Yuichiro Hayashi, Masahiro Oda, Takayuki Kitasaka, Kazunari Misawa, Kensaku Mori · 2022 · Computer Methods in Biomechanics and Biomedical Engineering Imaging & Visualization
  26. Self-supervised Depth Estimation from Spectral Consistency and Novel View Synthesis
    Yawen Lu, Guoyu Lu · 2022 · International Joint Conference on Neural Networks (IJCNN)
  27. Unsupervised Monocular Depth Estimation Based on Dual Attention Mechanism and Depth-Aware Loss
    Xinchen Ye, Mingliang Zhang, Rui Xu, Wei Zhong, Xin Fan, Zhu Liu, Jiaao Zhang · 2019 · IEEE International Conference on Multimedia and Expo (ICME)
  28. Efficient unsupervised monocular depth estimation using attention guided generative adversarial network
    Sumanta Bhattacharyya, Ju Shen, Stephen Welch, Chen Chen · 2021 · Journal of Real-Time Image Processing
  29. Predicting Unobserved Space for Planning via Depth Map Augmentation
    Marius Fehr, Tim Taubner, Yang Liu, Roland Siegwart, César Cadena · 2019 · International Conference on Advanced Robotics (ICAR)
  30. Generative Modeling for Multi-task Visual Learning
    Bao, Zhipeng, Martial Hebert, Yu-Xiong Wang · 2021 · arXiv (Cornell University)
  31. Deep Learning Approaches for 3D Model Generation from 2D Artworks to Aid Blind People with Tactile Exploration
    Rocco Furferi · 2024 · Heritage
  32. SRSA-Depth: shape and region similarity awareness for outdoor monocular depth estimation
    Liyue Ge, Congxuan Zhang, Zhen Chen, Ke Lu, Cheng Feng · 2025 · Multimedia Systems
  33. FLODCAST: Flow and depth forecasting via multimodal recurrent architectures
    Andrea Ciamarra, Federico Becattini, Lorenzo Seidenari, Alberto Del Bimbo · 2024 · Pattern Recognition
  34. AI in Surgical Robotics
    Samyakh Tukra, Niklas Lidströmer, Hutan Ashrafian, Stamatia Giannarou · 2021 · Springer eBooks
  35. Semantically guided self‐supervised monocular depth estimation
    Xiao Lu, Haoran Sun, Xiuling Wang, Zhiguo Zhang, Haixia Wang · 2022 · IET Image Processing
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    Zhongcheng Hong, Qiuxia Wu · 2022 · The Visual Computer
  37. FasterMDE: A real-time monocular depth estimation search method that balances accuracy and speed on the edge
    Dou ZiWen, Yuqi Li, Dong Ye · 2023 · Applied Intelligence
  38. Unsupervised single-shot depth estimation using perceptual reconstruction
    Christoph Angermann, Matthias Schwab, Markus Haltmeier, Christian Laubichler, Steinbjörn Jónsson · 2023 · Machine Vision and Applications
  39. RDRF-Net: A pyramid architecture network with residual-based dynamic receptive fields for unsupervised depth estimation
    Zhenyan Ji, Xiaojun Song, Houbin Song, Yang Hong, Xiaoxuan Guo · 2021 · Neurocomputing
  40. Unsupervised Monocular Depth Estimation Method Based on Multimodal Interaction Perception
    Xiaogang Song, Yuping Tan, Jingyu Ning, Xiaofeng Lu, Xinhong Hei · 2025 · IEEE Sensors Journal
  41. From Coarse to Fine: A Monocular Depth Estimation Model Based on Left-Right Consistency
    Zeyu Lei, Yan Wang, Yufan Xu, Rui Huang · 2019 · IEEE International Conference on Communication Technology (ICCT)
  42. Encoder-Decoder Structure with Multiscale Receptive Field Block for Unsupervised Depth Estimation from Monocular Video
    Songnan Chen, Junyu Han, Mengxia Tang, Ruifang Dong, Jiangming Kan · 2022 · Remote Sensing
  43. TP-GAN: Simple Adversarial Network With Additional Player for Dense Depth Image Estimation
    Andi Hendra, Yasushi Kanazawa · 2023 · IEEE Access
  44. AMENet is a monocular depth estimation network designed for automatic stereoscopic display
    Tianzhao Wu, Zhongyi Xia, Man Zhou, Ling Bing Kong, Zengyuan Chen · 2024 · Scientific Reports
  45. Monocular Depth and Ego-motion Estimation with Scale Based on Superpixel and Normal Constraints
    Junxin Lu, Yongbin Gao, Jieyu Chen, Jenq–Neng Hwang, Hamido Fujita, Zhijun Fang · 2024 · ACM Transactions on Multimedia Computing Communications and Applications
  46. A depth estimation framework based on unsupervised learning and cross-modal translation
    Jiafeng Shen, Kaiwei Wang, Kailun Yang, Kaite Xiang, Lei Fei, Xinxin Hu, Huabing Li, Hao Chen · 2019 · Target and Background Signatures
  47. Relativistic Approach for Training Self-Supervised Adversarial Depth Prediction Model Using Symmetric Consistency
    Hyeseung Park, Seung-Chul Park, Young Hoon Joo · 2020 · IEEE Access
  48. ARFF-VO: A Self-Supervised Monocular Visual Odometry With Adaptive Region-Based Feature Filtering in Dynamic Scenes
    Guofeng Tong, Yuanyang Zhang, Zheng Li, Jiaru Sun · 2025 · IEEE Sensors Journal
  49. Self-Supervised Monocular Depth Learning in Low-Texture Areas
    Wanpeng Xu, Ling Zou, Lingda Wu, Zhipeng Fu · 2021 · Remote Sensing
  50. Self-supervised Learning of PSMNet via Generative Adversarial Networks
    Xinyi Yang, Haifeng Lai, Bin Zou, Hang Fu, Qian Long · 2024 · Lecture notes in computer science
  51. Shading Meets Motion: Self-supervised Indoor 3D Reconstruction Via Simultaneous Shape-from-Shading and Structure-from-Motion
    Guoyu Lu · 2025 · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
  52. Discrete convolutional CRF networks for depth estimation from monocular infrared images
    Qianqian Wang, Haitao Zhao, Zhengwei Hu, Yuru Chen, Yuqi Li · 2020 · International Journal of Machine Learning and Cybernetics
  53. Face attribute analysis from structured light: an end-to-end approach
    Vikas Thamizharasan, Abhijit Das, Daniele Battaglino, François Brémond, Antitza Dantcheva · 2022 · Multimedia Tools and Applications
  54. Self-Supervised Learning of Depth Maps for Autonomous Cars
    Andrei-Sebastian Petrescu, Cristian Damian, Daniela Colţuc · 2023 · European Signal Processing Conference (EUSIPCO)
  55. Self-supervised neural network-based endoscopic monocular 3D reconstruction method
    Ziming Zhang, Wenjun Tan, Yuhang Sun, Juntao Han, Zhe Wang, Hongsheng Xue, Ruoyu Wang · 2023 · Health Information Science and Systems
  56. OnboardDepth: Depth Prediction for Onboard Systems
    Anelia Angelova, Devesh Yamparala, Justin Vincent, Chris Leger · 2019 · European Conference on Mobile Robots
  57. Self‐supervised binocular depth estimation algorithm with self‐rectification for autonomous driving
    Jingyao Bao, Hongfei Yu, Yongjia Zou, Jin Lv, Wei Liu, Yang Cao · 2024 · IET Intelligent Transport Systems
  58. High-Resolution Gated Depth Estimation for Self-Driving Cars in AdverseWeather
    Tobias Gruber, Stefanie Walz, Werner Ritter, Klaus Dietmayer · 2021 · Proceedings
  59. Improving Depth Estimation using Location Information
    Ahmed Zaitoon, Hossam E. Abd El Munim, Hazem M. Abbas · 2021 · International Conference on Computer Engineering & Systems (ICCES)
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    Samyakh Tukra, Niklas Lidströmer, Hutan Ashrafian, Stamatia Giannarou · 2022 · Springer eBooks
  61. R-LKDepth: Recurrent Depth Learning With Larger Kernel
    Zhongkai Zhou, Xinnan Fan, Pengfei Shi, Yuanxue Xin, Xiaotian Wang · 2024 · IEEE Signal Processing Letters
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    Ricardo Salvino Casado, Emerson Carlos Pedrino · 2024 · IEEE Latin America Transactions
  63. Binocular Stereovision
    Yu‐Jin Zhang · 2024 · Springer eBooks
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    Qingyu Zhang, Chunyan Wei, Qingxia Li, Xiaosen Tian, Chuanpeng Li · 2022 · IEEE International Conference on Smart Internet of Things (SmartIoT)
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    Saad Ali Imran, Muhammad Umar Karim Khan, Sikander Bin Mukarram, Chong‐Min Kyung · 2020 · arXiv (Cornell University)
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    Jaehoon Choi, Dongki Jung, Donghwan Lee, Changick Kim · 2020 · arXiv (Cornell University)
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    Xinchen Ye, Mingliang Zhang, Xin Fan, Rui Xu, Juncheng Pu, Ruoke Yan · 2020 · IEEE International Conference on Multimedia and Expo (ICME)
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    Muhammad Umar Karim Khan · 2021 · arXiv (Cornell University)
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