本文探讨了使用NeRF作为机器人视觉系统的一个新的监督来源,证明了一个场景的NeRF表示可以用来训练密集的物体描述符,所学的密集描述符使机器人能够准确地对薄而反光的物体进行6自由度(6-DoF)拾取和放置。 主页: https://yenchenlin.me/nerf-supervision 论文: https://ar
Mesh2NeRF extracts accurate radiance fields which provides direct supervision for training generative NeRFs and single scene representation. We validate the effectiveness of Mesh2NeRF across various tasks, achieving a noteworthy 3.12dB improvement in PSNR for view synthesis in single scene representation ...
EmerNeRF PyTorch implementation of: EmerNeRF: Emergent Spatial-Temporal Scene Decomposition via Self-Supervision, Jiawei Yang,Boris Ivanovic,Or Litany,Xinshuo Weng,Seung Wook Kim,Boyi Li,Tong Che,Danfei Xu,Sanja Fidler,Marco Pavone,Yue Wang
I am working on using gaussian splat models with data directly from 3D software - such as blender, and there i am able to generate my own .ply pointclouds and all necessary passes in order to start training. The idea here is to be able to use gsplat as an alternative way to render ...
Recently, Neural Radiance Fields(NeRF) have shown remarkable performance in the task of novel view synthesis through multi-view. The present study introduces an advanced optimization framework, termed Pose Interpolation Depth Supervision Neural Radiance Fields (PIDSNeRF), designed to address the ...