Occlusion-Aware Video Deblurring with a New Layered Blur Model
We present a deblurring method for scenes with occluding objects using a carefully designed layered blur model. Layered blur model is frequently used in the motion deblurring problem to handle locally varying blurs, which is caused by object motions or depth variations in a scene. However, conventional models have a limitation in representing the layer interactions occurring at occlusion boundaries. In this paper, we address this limitation in both theoretical and experimental ways, and propose a new layered blur model reflecting actual blur generation process. Based on this model, we develop an occlusion-aware deblurring method that can estimate not only the clear foreground and background, but also the object motion more accurately. We also provide a novel analysis on the blur kernel at object boundaries, which shows the distinctive characteristics of the blur kernel that cannot be captured by conventional blur models. Experimental results on synthetic and real blurred videos demonstrate that the proposed method yields superior results, especially at object boundaries.
Code (0)
등록된 구현이 없습니다.
Tasks
DeblurringObjectVideo DeblurringSimilar Papers 제목 키워드 기반
DAVIDE: Depth-Aware Video Deblurring
Video deblurring aims at recovering sharp details from a sequence of blurry frames. Despite the proliferation of depth sensors in mobile phones and the potential of depth information to guide deblurring, depth-aware debl…
DeblurringVideo DeblurringRethinking Video Deblurring with Wavelet-Aware Dynamic Transformer and Diffusion Model
Current video deblurring methods have limitations in recovering high-frequency information since the regression losses are conservative with high-frequency details. Since Diffusion Models (DMs) have strong capabilities i…
DeblurringVideo DeblurringFrequency-aware Event-based Video Deblurring for Real-World Motion Blur
Video deblurring aims to restore sharp frames from blurred video clips. Despite notable progress in video deblurring works it is still a challenging problem because of the loss of motion information during the durati…
DeblurringVideo AlignmentVideo DeblurringAggregating Nearest Sharp Features via Hybrid Transformers for Video Deblurring
Video deblurring methods, aiming at recovering consecutive sharp frames from a given blurry video, usually assume that the input video suffers from consecutively blurry frames. However, in real-world scenarios captured b…
DeblurringVideo DeblurringMotion Deblurring in the Wild
The task of image deblurring is a very ill-posed problem as both the image and the blur are unknown. Moreover, when pictures are taken in the wild, this task becomes even more challenging due to the blur varying spatiall…
DeblurringImage Deblurring