In this article, we design a portrait detailed decoding module to compensate for local features (like some hair details) that are missing in Transformer [1].
To achieve the effective excavation of both local and global features, we design a semi-supervised network that leverages Transformer to capture the global ...
Mar 1, 2023 · To achieve the effective excavation of both local and global features, we design a semi-supervised network that leverages Transformer to capture ...
Dec 8, 2022 · We design a semi-supervised network (ASSN) with two kinds of innovative adaptive strategies for portrait matting.
Jul 26, 2023 · This paper first proposes a semi-supervised deep learning matting algorithm based on semantic consistency of trimaps (Tri-SSL), which uses trimaps to provide ...
Semi-Supervised Portrait Matting via the Collaboration of Teacher ... - OUCI
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Zhang, Semi-supervised portrait matting using transformer, Digit. Signal ... Matting Algorithm with Improved Portrait Details for Images with Complex Backgrounds.
Aug 16, 2024 · The masked-reconstruction task is used to pre-train the Transformer-based context network before semi-supervised based fine-tuning. The global- ...
Dec 6, 2022 · We design a semi-supervised network (ASSN) with two kinds of innovative adaptive strategies for portrait matting.
Aug 15, 2023 · Image matting refers to precisely estimating the foreground opacity mattes from a given image. It is a necessary task in the computer vision ...
We propose a semi-supervised network for wide-angle portraits correction. Wide-angle images often suffer from skew and distortion affected by perspective ...
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