Stable Autofocus with Focal Consistency Loss

Sangwon Lee, Myungsub Choi, Nagyeong Lee, Hyong-Euk Lee; Proceedings of the Winter Conference on Applications of Computer Vision (WACV), 2025, pp. 640-649

Autofocus aims to accurately position the camera lens to bring the desired region of interest into focus. Conventional works search for the sharpest frame within the lens movement. However sharpness measure in many real-world settings is ambiguous and may cause a focus hunting problem where the lens continuously moves back and forth to search for the accurate position. To mitigate this problem we introduce a simple yet powerful loss function specifically designed to produce consistent outputs in autofocus systems. The proposed Focal Consistency Loss (FCL) allows autofocus models to better learn the geometric cues relative to each initial position of the lens significantly reducing distracting lens movement and enhancing the user experience when taking a photo. Furthermore we improve autofocus stability by utilizing multiple consecutive frames in a practical way. Experimental results show the effectiveness of FCL in various practical scenarios including multi-frame autofocus for both conventional and dual-pixel images.