weihaox/awesome-neural-rendering - GitHub
Resources of Neural Rendering. Contribute to weihaox/awesome-neural-rendering development by creating an account on GitHub.
Neural Rendering for Autonomous Driving - GitHub
This is the official code release of the CVPR 2024 paper NeuRAD: Neural Rendering for Autonomous Driving, building on top of Nerfstudio. Besides releasing the code for our NeuRAD model, we hope that this can lay the ground-work for research on applying neural rendering methods in autonomous driving ...
GitHub - DNA-Rendering/DNA-Rendering: DNA-RENDERING: A …
May 13, 2024 · In this work, we present DNA-Rendering, a large-scale, high-fidelity repository of human performance data for neural actor rendering. DNA-Rendering presents several alluring attributes. First, our dataset contains over 1500 human subjects, 5000 motion sequences, and 67.5M frames' data volume.
zzw-zwzhang/Awesome-of-Neural-Rendering - GitHub
Deferred Neural Rendering: Image Synthesis using Neural Textures: SIGGRAPH: Other: PyTorch(Author) 123: Geometry-Aware Neural Rendering: NeurIPS: Other: PyTorch(Author) `` Scene Representation Networks: Continuous3D-Structure-Aware Neural Scene Representations: NeurIPS-Oral: Other: PyTorch(Author) 287: Monocular Neural Image Based Rendering ...
GitHub - awesome-NeRF/awesome-NeRF: A curated list of …
DONeRF: Towards Real-Time Rendering of Compact Neural Radiance Fields using Depth Oracle Networks, Neff et al., CGF 2021 | github | bibtex; FastNeRF: High-Fidelity Neural Rendering at 200FPS, Garbin et al., Arxiv 2021 | bibtex; KiloNeRF: Speeding up Neural Radiance Fields with Thousands of Tiny MLPs , Reiser et al., ICCV 2021 | github | bibtex
BokehMe: When Neural Rendering Meets Classical Rendering …
This repository is the official PyTorch implementation of the CVPR 2022 paper "BokehMe: When Neural Rendering Meets Classical Rendering". NOTE: There is a citation mistake in the paper of the conference version. In section 4.1, the disparity …
Hybrid Neural Rendering for Large-Scale Scenes with Motion Blur
Our method takes advantage of both neural 3D representation and image-based rendering to render high-fidelity and temporally consistent results. Specifically, the image-based features compensate for the defective neural 3D features, and the neural 3D features boost the temporal consistency of image ...
GitHub - RenYurui/PIRender: The source code of the ICCV2021 …
The source code of the ICCV2021 paper "PIRenderer: Controllable Portrait Image Generation via Semantic Neural Rendering" (ICCV2021) The proposed PIRenderer can synthesis portrait images by intuitively controlling the face motions with fully disentangled 3DMM parameters.
GitHub - alievk/npbg: Neural Point-Based Graphics
This is PyTorch implementation of Neural Point-Based Graphics (NPBG), a new method for realtime photo-realistic rendering of real scenes. NPBG uses a raw point cloud as the geometric representation of a scene, and augments each point with a learnable neural descriptor that encodes local geometry and appearance.
GitHub - yangjiheng/nerf_and_beyond_docs
May 8, 2023 · Neural rendering is closely related, and combines ideas from classical computer graphics and machine learning to create algorithms for synthesizing images from real-world observations. Neural rendering is a leap forward towards the goal of synthesizing photo-realistic image and video content.