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Reversing the Cycle: Self-supervised Deep Stereo Through Enhanced Monocular Distillation.

, , , , and . ECCV (11), volume 12356 of Lecture Notes in Computer Science, page 614-632. Springer, (2020)

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Self-adapting Confidence Estimation for Stereo., , , , and . ECCV (24), volume 12369 of Lecture Notes in Computer Science, page 715-733. Springer, (2020)Generative Adversarial Networks for Unsupervised Monocular Depth Prediction., , , and . ECCV Workshops (1), volume 11129 of Lecture Notes in Computer Science, page 337-354. Springer, (2018)Monocular Depth Perception on Microcontrollers for Edge Applications., , , , , , and . IEEE Trans. Circuits Syst. Video Technol., 32 (3): 1524-1536 (2022)Sensor-Guided Optical Flow., , and . ICCV, page 7888-7898. IEEE, (2021)Unsupervised confidence for LiDAR depth maps and applications., , , and . IROS, page 8352-8359. IEEE, (2022)Enabling monocular depth perception at the very edge., , , , , , and . CVPR Workshops, page 1581-1583. Computer Vision Foundation / IEEE, (2020)Real-Time Self-Supervised Monocular Depth Estimation Without GPU., , , and . IEEE Trans. Intell. Transp. Syst., 23 (10): 17342-17353 (2022)On the confidence of stereo matching in a deep-learning era: a quantitative evaluation., , , , , , , and . CoRR, (2021)Real-Time Single Image Depth Perception in the Wild with Handheld Devices., , , , , and . Sensors, 21 (1): 15 (2021)Learning End-to-End Scene Flow by Distilling Single Tasks Knowledge., , , and . AAAI, page 10435-10442. AAAI Press, (2020)