Multiscale Tensor Decomposition and Rendering Equation Encoding for View Synthesis

Rendering novel views from captured multi-view images has made considerable progress since the emergence of the neural radiance field. This paper aims to further advance the quality of view synthesis by proposing a novel approach dubbed the neural radiance feature field (NRFF). We first propose a multiscale tensor decomposition scheme to organize learnable features so as to represent scenes from coarse to fine scales. We demonstrate many benefits of the proposed multiscale representation, including more accurate scene shape and appearance reconstruction, and faster convergence compared with the single-scale representation. Instead of encoding view directions to model view-dependent effects, we further propose to encode the rendering equation in the feature space by employing the anisotropic spherical Gaussian mixture predicted from the proposed multiscale representation. The proposed NRFF improves state-of-the-art rendering results by over 1 dB in PSNR on both the NeRF and NSVF synthetic datasets. A significant improvement has also been observed on the real-world Tanks & Temples dataset. Code can be found at https://github.com/imkanghan/nrff

Arbitrary beam control using passive lossless metasurfaces enabled by orthogonally-polarized custom surface waves

For passive, lossless impenetrable metasurfaces, a design technique for arbitrary beam control of receiving, guiding, and launching is presented. Arbitrary control is enabled by a custom surface wave in an orthogonal polarization such that its addition to the incident (input) and the desired scattered (output) fields is supported by a reactive surface impedance everywhere on the reflecting surface. Such a custom surface wave (SW) takes the form of an evanescent wave propagating along the surface with a spatially varying envelope. A growing SW appears when an illuminating beam is received. The SW amplitude stays constant when power is guided along the surface. The amplitude diminishes as a propagating wave (PW) is launched from the surface as a leaky wave. The resulting reactive tensor impedance profile may be realized as an array of anisotropic metallic resonators printed on a grounded dielectric substrate. Illustrative design examples of a Gaussian beam translator-reflector, a probe-fed beam launcher, and a near-field focusing lens are provided

Texture Mixer: A Network for Controllable Synthesis and Interpolation of Texture

This paper addresses the problem of interpolating visual textures. We formulate this problem by requiring (1) by-example controllability and (2) realistic and smooth interpolation among an arbitrary number of texture samples. To solve it we propose a neural network trained simultaneously on a reconstruction task and a generation task, which can project texture examples onto a latent space where they can be linearly interpolated and projected back onto the image domain, thus ensuring both intuitive control and realistic results. We show our method outperforms a number of baselines according to a comprehensive suite of metrics as well as a user study. We further show several applications based on our technique, which include texture brush, texture dissolve, and animal hybridization.Comment: Accepted to CVPR'1