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 …

Human matting is a foundation task in image and video processing where human
foreground pixels are extracted from the input. Prior works either improve the accuracy by …

Real-time video matting on edge devices faces significant computational resource
constraints, limiting the widespread use of video matting in applications such as online …

Recent advancements in Multimodal Large Language Models (LLMs) have focused
primarily on scaling by increasing text-image pair data and enhancing LLMs to improve …

Recently, real-time video matting has received growing attention from academia and
industry as a new research area on the rise. However, most current state-of-the-art solutions …

The creation of high-quality alpha mattes as ground-truth data for video matting is typically a
laborious task. The trade-off between accuracy manual corrections and capture constraints …

The most recent efforts in video matting have focused on eliminating trimap dependency
since trimap annotations are expensive and trimap-based methods are less adaptable for …

Virtual production, a filmmaking technique that seamlessly merges virtual and real
cinematography, has revolutionized the film and television industry. However, traditional …

Conventional video matting outputs one alpha matte for all instances appearing in a video
frame so that individual instances are not distinguished. While video instance segmentation …

Real-time video matting is essential for applications like online video conferencing but faces
challenges in human-object interaction (HOI) scenarios, known as the HOI-matting problem …