InCaRPose: In-Cabin Relative Camera Pose Estimation Model and Dataset
Camera extrinsic calibration is a fundamental task in computer vision. However, precise relative pose estimation in constrained, highly distorted environments, such as in-cabin automotive monitoring (ICAM), remains challenging. We present InCaRPose, a Transformer-based architecture designed for robust relative pose prediction between image pairs, which can be used for camera extrinsic calibration. By leveraging frozen backbone features such as DINOv3 and a Transformer-based decoder, our model effectively captures the geometric relationship between a reference and a target view. Unlike traditional methods, our approach achieves absolute metric-scale translation within the physically plausi...
| Authors | Felix Stillger, Lukas Hahn, Frederik Hasecke et al. |
|---|---|
| Primary category | cs.CV |
| Published | 4 April 2026 |
| Last updated at source | 4 April 2026 |
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