Novel View Synthesis Using NeRF
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Updated
Jan 11, 2024 - Jupyter Notebook
Novel View Synthesis Using NeRF
Neural Rendering for 3D Reconstruction and View Synthesis: An Overview
Neural Radiance Fields - generating new perspectives of intricate scenes by refining a continuous volumetric scene representation through a limited selection of input views.
neural radiance fields for novel view synthesis and 3d reconstruction
Code implementation for NeRF and DietNeRF papers. NeRF presents a method for synthesizing novel views of complex 3D scenes by optimizing an underlying continuous volumetric scene function using a sparse set of input views.
✭ MAGNETRON ™ ✭: Implementation of Google's Dreambooth (with Stable Diffusion model) instead of IMAGEN (for making MAGNETRON ™ TECHNOLOGY IMAGINATION PROXIA). In particular this can be used to mimic the appearance of subjects in a given reference set and synthesize novel renditions of them in different contexts.
Neural Radiance Fields
Deep View Synthesis via Self-Consistent Generative Networks (TMM 2021)
PyTorch code for ICPR 2020 paper "Future Urban Scene Generation Through Vehicle Synthesis"
Meta-Learning for Neural Implicit Surface of Object Categories
NeRF for Dynamic Scenes
Code for my point cloud completion paper in CVF-ICCV2017
NeRF implementation with minimal code and maximal readability using PyTorch
Learning Vision Based Autonomous Lateral Vehicle Control without Supervision
[ICLR 2024] Official implementation of "Pseudo-Generalized Dynamic View Synthesis from a Video"
Code accompanying CVPR 2022 paper, " SOMSI: Spherical Novel View Synthesis with Soft Occlusion Multi-Sphere Images"
[NeurIPS 2023] Implementation of "Template-free Articulated Neural Point Clouds for Reposable View"
This repository is used to collect NeRF papers on autonomous driving
Depth Image Based Rendering Algorithm Implementation in MATLAB. For hole filling, impainting algorithm with fast marching method (FMM) known as TELEA algorithm has been used
An unofficial Unity port of the MERF viewer
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