J Li, J Jain, H Shi - … of the IEEE/CVF Conference on …, 2024 - openaccess.thecvf.com
In this paper we propose the Matting Anything Model (MAM) an efficient and versatile framework for estimating the alpha matte of any instance in an image with flexible and …
We introduce a real-time, high-resolution background replacement technique which operates at 30fps in 4K resolution, and 60fps for HD on a modern GPU. Our technique is …
S Lin, L Yang, I Saleemi… - Proceedings of the IEEE …, 2022 - openaccess.thecvf.com
We introduce a robust, real-time, high-resolution human video matting method that achieves new state-of-the-art performance. Our method is much lighter than previous approaches and …
GT Park, SJ Son, JY Yoo, SH Kim… - Proceedings of the …, 2022 - openaccess.thecvf.com
In this paper, we propose a transformer-based image matting model called MatteFormer, which takes full advantage of trimap information in the transformer block. Our method first …
J Li, J Zhang, D Tao - arXiv preprint arXiv:2304.04672, 2023 - arxiv.org
Image matting refers to extracting precise alpha matte from natural images, and it plays a critical role in various downstream applications, such as image editing. Despite being an ill …
Existing portrait matting methods either require auxiliary inputs that are costly to obtain or involve multiple stages that are computationally expensive, making them less suitable for …
Image matting is an inverse fusion process that separates the foreground and background information by predicting alpha matte for each pixel. Recently, plain vision Transformers …
Abstract We propose Mask Guided (MG) Matting, a robust matting framework that takes a general coarse mask as guidance. MG Matting leverages a network (PRN) design which …
Y Sun, CK Tang, YW Tai - … of the IEEE/CVF Conference on …, 2021 - openaccess.thecvf.com
Natural image matting separates the foreground from background in fractional occupancy which can be caused by highly transparent objects, complex foreground (eg, net or tree) …