综上,HeadNeRF的损失定义为: 参考文献 原文链接:HeadNeRF: A Real-Time NeRF-Based Parametric Head Model | CVPR 2022 Zhanghan Ke, Jiayu Sun, Kaican Li, Qiong Yan, and Rynson W.H. Lau. Modnet: Real-time trimap-free portrait matting via objective decomposition. In AAAI, 2022. 4 Changqian Yu...
This repository contains a pytorch implementation of "HeadNeRF: A Real-time NeRF-based Parametric Head Model (CVPR 2022)". Authors:Yang Hong, Bo Peng, Haiyao Xiao,Ligang LiuandJuyong Zhang*. |Project Page|Paper| This code has been tested on ubuntu 20.04/18.04 and contains the following parts...
HeadNeRF: A Real-time NeRF-based Parametric Head Model. Yang Hong, Peng Bo, Haiyao Xiao, Ligang Liu, Juyong Zhang. arxiv 2021. [PDF] [Project]PERF: Performant, Explicit Radiance Fields. Sverker Rasmuson, Erik Sintorn, Ulf Assarsson. arxiv 2021. [PDF]BungeeNeRF: Progressive Neural ...
In the field of autopilot, the radiation field can reconstruct 3D scenes and perform rendering in real time by deconstructing the interaction between light and the surface material of the environmental target. The strategy of NeRF to reconstruct a 3D scene is to not directly use the explicit scen...
Specifically, we use FLAME (Li et al., 2017) to build a statistical 3D head model \({\mathcal {M}}\) from the surface normal \({\hat{N}}\) and albedo \({\hat{A}}\). First, we fit the parametric 3D face model from FLAME onto the input image by using a ResNet-based ...
5.1.1 3D-based facial reenactment 3D parametric model-based approach The practice of reenactment is not new and has a long his- tory. High-quality results were obtained using 3D parametric models even before deep learning-based deepfake reenactment was developed [45, 46]. Eventually, these ...
Im avatar: Implicit morphable head avatars from videos. In Pro- ceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 13545–13555, 2022. 3 [58] Zerong Zheng, Tao Yu, Yebin Liu, and Qionghai Dai. Pamir: Parametric model-condition...
2022 [HeadNeRF] HeadNeRF: A Real-time NeRF-based Parametric Head Model CVPR 2022 Code Project - 2022 [SSP-NeRF] Semantic-Aware Implicit Neural Audio-Driven Video Portrait Generation Arxiv 2022 Code Project - 2021 [AD-NeRF] AD-NeRF: Audio Driven Neural Radiance Fields for Talking Head Synthes...
CST-Stereo: "Consistency-aware Self-Training for Iterative-based Stereo Matching", Zhou et al.,CVPR, 2025. [Paper] [Bibtex] [Google Scholar] Online Continual Adaptation 🚩 MadNet: "Real-Time Self-Adaptive Deep Stereo", Tonioni et al., CVPR, 2019. [Paper] [Code] [Bibtex] [Google ...
combined with the necessity for real-time performance on resource-constrained devices, has further complicated the task. These challenges have led to the development of more robust, versatile, and efficient deep stereo models that effectively address these limitations and improve their practical applicatio...