Portrait matting using an attention-based memory network - Song, Shufeng (Nanyang Technological University, 2023)
Matting is the process of generating prediction alpha and foreground with rich details from the input images. There are three major challenges for traditional matting algorithms. Firstly, most of them focus on auxiliary-based matting, while putting those algorithms into daily use is impractical since additional input is not applicable in most scenarios. The second thing is the construction of temporal-guided modules to exploit temporal coherence for video matting tasks. Last but not least is the availability of matting datasets. This thesis addresses the above challenges and proposes a novel auxiliary-free video matting network.