没错,而且还是不用3D建模的那种。这就是来自伯克利大学和谷歌的最新研究:NeRF,只需要输入少量静态图片,就能做到多视角的逼真3D效果。还需要专门说明的是,这项研究的代码和数据,也都已经开源。你有想法,尽情一试~静态图片,合成逼真3D效果 我们先来看下NeRF,在合成数据集(synthetic dataset)上的效果。可以看到...
tensorflow_time_series_dataset-0.1.0-py3-none-any.whl 2024-10-10 09:16:00 积分:1 tensorflow_qnd-0.0.8-py3.5.egg 2024-10-10 09:14:12 积分:1 tensorflow_serving_api_python3-1.6.0-py2.py3-none-any.whl 2024-10-10 09:13:14 ...
请参阅Kitti Dataset网站或文件夹下Github上的代码以了解数据格式。 剩下的部分,我们首先需要讨论传感器安装相关的问题,通过Kitti对象检测数据集来了解数据结构,并通过如何进行校准以了解校准矩阵。接下来,将详细介绍3D-2D和2D-3D投影映射,最后以可视化的方式显示激光雷达与摄像机...
This work generates a valuable outcrop dataset and original discussions of DIA at different image scales for input modeling to match ultrasonic and elastic properties with the lithological characteristics of Oman samples.doi:10.1016/j.marpetgeo.2018.08.004Lima Neto Irineu A....
4.1 Analysis of training on each dataset 首先在每个数据集上训练ResNet-18,根据之前的工作,在UCF-101,HMDB-51和ActivityNet上训练的3D CNN没有达到高精度,而在Kinetics上训练的3D CNN效果很好,试图重现这样的结果。在这个过程中,使用UCF-101和HMDB-51的split1,以及ActivityNet和Kinetics的训练集和验证集。图4显示...
Using serial block-face imaging, we recorded the 3D folding pattern of the horn primordia in vivo as a 3D volume dataset (Fig. S1). To that end, fresh dissected tissue was embedded in a matrix for cryostat sectioning, whereupon the surface of the compound block (not a sliced tissue layer...
we propose a diffusion-based SLP model trained on a curated large-scale dataset of 4D signing avatars and their corresponding text transcripts. The proposed method can generate dynamic sequences of 3D avatars from an unconstrained domain of discourse using a diffusion process formed on a novel and...
Prepare your own dataset We follow the dataset format of EG3Dhere. You can obtain the segmentation masks of your own dataset byDINO clustering, and obtain the edge map bypidinetandinformative drawing. Citation If you find this repository useful for your research, please cite the following work...
KITTI-360 is a suburban driving dataset which comprises richer input modalities, comprehensive semantic instance annotations and accurate localization to facilitate research at the intersection of vision, graphics and robotics. For efficient annotation, we created a tool to label 3D scenes with bounding ...
To run MNIST demo: Go into the folder 'Demo/MNIST' , Run 'demoMnist.m' file. The file will download MNIST dataset and start training the network. After 15 iterations (several minutes) it will open a GUI where you can test the network performance. In addition layer 1 filters will be ...