Woonghyun Ka — accepted AI-conference papers

2024

Modeling Stereo-Confidence out of the End-to-End Stereo-Matching Network via Disparity Plane Sweep

Jae Young Lee, Woonghyun Ka, Jaehyun Choi, Junmo Kim

AAAI 2024technical

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. Grounded in the foundational concepts of disparity definiti…

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2024

Stereo-Matching Knowledge Distilled Monocular Depth Estimation Filtered by Multiple Disparity Consistency

Woonghyun Ka, Jae Young Lee, Jaehyun Choi, Junmo Kim

ICASSP 2024accepted

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. In these methods, the learning-based stereo-confidence network is generally utilized to…

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