Title:	Lightweight single image dehazing utilizing relative depth information
Authors:	Frasiolas, Panagiotis Reppas, Asterios Konstantoudakis, Konstantinos Zarpalos, Dimitrios
Citation:	WSCG 2024: full papers proceedings: 32. International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision, p. 349-358.
Issue Date:	2024
Publisher:	Václav Skala - UNION Agency
Document type:	konferenční příspěvek conferenceObject
URI:	http://hdl.handle.net/11025/57409
ISSN:	2464–4625 (online) 2464–4617 (print)
Keywords:	lehká váha;transformátory vidění;relativní hloubka;dehazování
Keywords in different language:	lightweight;vision transformers;relative depth;dehazing
Abstract in different language:	Considering the need for lightweight and fast implementations, this paper presents an architecture based on a Mo bileVit encoder for efficiency and speed, introducing a fully convolutional lightweight decoder with skip connec tions for feature extraction. The main purpose of this network is to address the problem of single image dehazing. Recognizing the critical role of depth information in assisting the above task, the merging of these two tasks into a single network was performed in a supervised manner. Taking into account that there is a shortage of datasets that provide both dehazing and relative depth estimation ground truths, Depth Anything was utilized to extract the relative depth values of the images, which is the SOTA network in this task
Rights:	© Václav Skala - UNION Agency
Appears in Collections:	WSCG 2024: Full Papers Proceedings

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