High-Order Nonparametric Belief-Propagation for Fast Image Inpainting

Semi-parametric Image Inpainting

This paper introduces a semi-parametric approach to image inpainting for irregular holes. The nonparametric part consists of an external image database. During test time database is used to retrieve a supplementary image, similar to the input masked picture, and utilize it as auxiliary information for the deep neural network. Further, we propose a novel method of generating masks with irregular holes and present public dataset with such masks. Experiments on CelebA-HQ dataset show that our semi-parametric method yields more realistic results than previous approaches, which is confirmed by the …

Pull Message Passing for Nonparametric Belief Propagation

We present a "pull" approach to approximate products of Gaussian mixtures within message updates for Nonparametric Belief Propagation (NBP) inference. Existing NBP methods often represent messages between continuous-valued latent variables as Gaussian mixture models. To avoid computational intractability in loopy graphs, NBP necessitates an approximation of the product of such mixtures. Sampling-based product approximations have shown effectiveness for NBP inference. However, such approximations used within the traditional "push" message update procedures quickly become computationally prohibi…

Image Completion for View Synthesis Using Markov Random Fields and Efficient Belief Propagation

View synthesis is a process for generating novel views from a scene which has been recorded with a 3-D camera setup. It has important applications in 3-D post-production and 2-D to 3-D conversion. However, a central problem in the generation of novel views lies in the handling of disocclusions. Background content, which was occluded in the original view, may become unveiled in the synthesized view. This leads to missing information in the generated view which has to be filled in a visually plausible manner. We present an inpainting algorithm for disocclusion filling in synthesized views based …

The Best of Both Worlds: Combining Model-based and Nonparametric Approaches for 3D Human Body Estimation

Nonparametric based methods have recently shown promising results in reconstructing human bodies from monocular images while model-based methods can help correct these estimates and improve prediction. However, estimating model parameters from global image features may lead to noticeable misalignment between the estimated meshes and image evidence. To address this issue and leverage the best of both worlds, we propose a framework of three consecutive modules. A dense map prediction module explicitly establishes the dense UV correspondence between the image evidence and each part of the body mo…

用于计算摄影、图像合成与对抗防御的深度非参数凸化滤波

Deep Nonparametric Convexified Filtering for Computational Photography, Image Synthesis and Adversarial Defense

提出深度非参数凸化滤波（DNCF）框架，通过非参数网络模拟图像形成物理方程，实现计算摄影图像恢复，具有强泛化性、对抗鲁棒性及10倍加速，可实时防御图像分类对抗攻击。