Street Gaussians的算法流程如图所示。 类似于 MARS,Street Gaussians 通过标注将场景背景和动态车辆分离,并分别建模。不同之处在于,Street Gaussians 使用三维高斯对各模块进行建模,并生成各三维高斯的位置、透明度、协方差等信息。在颜色外观方面,背景被指定了球谐函数系数,而动态车辆则绑定了一个四维球谐函数模型。因...
conda create --name street-gaussians-ns -y python=3.8 conda activate street-gaussians-ns pip install --upgrade pip Dependencies Install PyTorch with CUDA (this repo has been tested with CUDA 11.8) andtiny-cuda-nn.cuda-toolkitis required for buildingtiny-cuda-nn. ...
将场景显式分解为单独的代理可以单独控制它们。这些代理可以表示为场景图中的边界框,如神经场景图(NSG),该图在UniSim、MARS、NeuRAD、ML-NSG和最近的基于高斯的作品StreetGaussians、DrivingGaussians和HUGS中被广泛采用。然而,由于时间无关表示的限制或基于变形的技术的限制,这些方法仅处理刚性目标。为了解决这些问题,O...
GitHub链接: https://github.com/LightwheelAI/street-gaussians-ns论文链接: https://arxiv.org/abs/2401.01339目前3DGS在自动驾驶领域已经有了不少应用的工作,street gaussians是其中比较有影响力的工作,我…
这些代理可以表示为场景图中的边界框,如神经场景图(NSG),该图在UniSim、MARS、NeuRAD、ML-NSG和最近的基于高斯的作品StreetGaussians、DrivingGaussians和HUGS中被广泛采用。然而,由于时间无关表示的限制或基于变形的技术的限制,这些方法仅处理刚性目标。为了解决这些问题,OmniRe提出了一种高斯场景图,该图结合了刚性和...
such growth would be an indication of inverse incompressible energy transfer. Another example of such a finite-size effect can be found in Ref.[58], where a simulation of a trapped BEC stirred by aGaussianpotential of width∼4ξis performed. Different stirring regimes were found based on the...
Page](https://zju3dv.github.io/street_gaussians) | [Paper](https://arxiv.org/pdf/2401.01339.pdf) | [Data](https://drive.google.com/file/d/1IJSFVGxwLLKLP8uidfUTGzb8n7nNDuIi/view?usp=drive_link) | [Unofficial Implementation](https://github.com/LightwheelAI/street-gaussians-ns) ...
We tried to apply a fully connected CRF with Gaussian kernel, as introduced by Kra¨henbu¨hl and Koltun [30]. We used the standard appearance and smoothness kernels and tuned parameters on the valida- tion set by running several thousand Hyperopt iterations [5]. Applying this post ...
Traditional techniques include Gaussian mixture models [27], recurrent neural network (RNN)with bidirectional long short-term memory (LSTM) cells [28], deep learning [29] and CNNs [30]. The current state of the art for indoor and outdoor gesture recognition builds on deep neural networks. A...
Instead of directly supplying 𝑆̂(𝑁)=𝑒𝑁(𝑆)S^(N)=eN(S) to 𝑑𝑁dN, the output of the encoder is interpreted as the mean and variance of a Gaussian distribution. Samples of this distribution are fed into 𝑑𝑁dN, subsequently. Similarly, an ANN transforming uncorrelated ...