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SPL Volume 30 | 2023

Fine-Scale Face Fitting and Texture Fusion With Inverse Renderer

3D face reconstruction from a single image still suffers from low accuracy and inability to recover textures in invisible regions. In this paper, we propose a method for generating a 3D portrait with complete texture. The coarse face-and-head model and texture parameters are obtained using 3D Morphable Model fitting. We design an image-geometric inverse renderer that acquires normal, albedo, and light to jointly reconstruct the facial details.

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Improved RIC Bounds in Terms of δ2s for Hard Thresholding-Based Algorithms

Iterative hard thresholding (IHT) and hard thresholding pursuit (HTP) are two kinds of classical hard thresholding-based algorithms widely used in compressed sensing. Restricted isometry constant (RIC) of sensing matrix which ensures the convergence of iterative algorithms plays a key role in guaranteeing successful recovery. In the analysis of sufficient condition to ensure recovery performance, the RIC δ3s is generally used in previous literature, while δ2s is rarely addressed. In this letter, we first show that the theoretical optimal step-length is 1 while using sufficient condition in terms of δ2s .

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Learning Adaptive Sparse Spatially-Regularized Correlation Filters for Visual Tracking

The correlation filter(CF)-based tracker is a classic and effective model in the field of visual tracking. For a long time, most CF-based trackers solved filters using only ridge regression equations with l2 -norm, which can make the trained model noisy and not sparse. As a result, we propose a model of adaptive sparse spatially-regularized correlation filters (AS2RCF). Aiming to suppress the noise mixed in the model, we improve it by introducing an l1 -norm spatial regularization term. 

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Deep Image Registration With Depth-Aware Homography Estimation

Image registration is a basic task in computer vision, for its wide potential applications in image stitching, stereo vision, motion estimation, and etc. Most current methods achieve image registration by estimating a global homography matrix between candidate images with point-feature-based matching or direct prediction. However, as real-world 3D scenes have point-variant photograph distances (depth), a unified homography matrix is not sufficient to depict the specific pixel-wise relations between two images.

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