Fast Multi-Level Foreground Estimation
원문 초록
Alpha matting aims to estimate the translucency of an object in a given image. The resulting alpha matte describes pixel-wise to what amount foreground and background colors contribute to the color of the composite image. While most methods in literature focus on estimating the alpha matte, the process of estimating the foreground colors given the input image and its alpha matte is often neglected, although foreground estimation is an essential part of many image editing workflows. In this work, we propose a novel method for foreground estimation given the alpha matte. We demonstrate that our fast multi-level approach yields results that are comparable with the state-of-the-art while outperforming those methods in computational runtime and memory usage.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
MaSS13K: A Matting-level Semantic Segmentation Benchmark
VRMDiff: Text-Guided Video Referring Matting Generation of Diffusion
BEN: Using Confidence-Guided Matting for Dichotomous Image Segmentation
ReFlow6D: Refraction-Guided Transparent Object 6D Pose Estimation via Intermediate Representation Learning
Memory Efficient Matting with Adaptive Token Routing
ZIM: Zero-Shot Image Matting for Anything
토론
이 논문과 연결된 포럼 글이 아직 없습니다.