no code implementations • 22 Jan 2024 • Woonghyun Ka, Jae Young Lee, Jaehyun Choi, Junmo Kim
In stereo-matching knowledge distillation methods of the self-supervised monocular depth estimation, the stereo-matching network's knowledge is distilled into a monocular depth network through pseudo-depth maps.
no code implementations • 22 Jan 2024 • Jae Young Lee, Woonghyun Ka, Jaehyun Choi, Junmo Kim
We propose a novel stereo-confidence that can be measured externally to various stereo-matching networks, offering an alternative input modality choice of the cost volume for learning-based approaches, especially in safety-critical systems.
3 code implementations • 19 Jan 2022 • Doyeon Kim, Woonghyun Ka, Pyungwhan Ahn, Donggyu Joo, Sehwan Chun, Junmo Kim
Depth estimation from a single image is an important task that can be applied to various fields in computer vision, and has grown rapidly with the development of convolutional neural networks.
Ranked #24 on Monocular Depth Estimation on KITTI Eigen split