In this work, we present a novel framework built to simplify 3D asset generation for amateur users. To enable interactive generation, our method supports a variety of input modalities …
Implicit neural fields, typically encoded by a multilayer perceptron (MLP) that maps from coordinates (eg, xyz) to signals (eg, signed distances), have shown remarkable promise as …
Existing 3D-aware facial generation methods face a dilemma in quality versus editability: they either generate editable results in low resolution, or high-quality ones with no editing …
Abstract 3D-aware generative adversarial networks (GANs) synthesize high-fidelity and multi-view-consistent facial images using only collections of single-view 2D imagery …
J Xie, H Ouyang, J Piao, C Lei… - Proceedings of the …, 2023 - openaccess.thecvf.com
We present a high-fidelity 3D generative adversarial network (GAN) inversion framework that can synthesize photo-realistic novel views while preserving specific details of the input …
Recent years have seen remarkable progress in deep learning powered visual content creation. This includes deep generative 3D-aware image synthesis, which produces high …
Inverse graphics aims to recover 3D models from 2D observations. Utilizing differentiable rendering, recent 3D-aware generative models have shown impressive results of rigid object …
We address the problem of learning person-specific facial priors from a small number (eg, 20) of portrait photos of the same person. This enables us to edit this specific person's facial …
Abstract We propose LIRF (Local Implicit Ray Function), a generalizable neural rendering approach for novel view rendering. Current generalizable neural radiance fields (NeRF) …