2024年12月4日 · In this paper, we introduce 2DGS-Room, a novel method leveraging 2D Gaussian Splatting for high-fidelity indoor scene reconstruction. Specifically, we employ a seed-guided mechanism to control the distribution of 2D Gaussians, with the density of seed points dynamically optimized through adaptive growth and pruning mechanisms.

In this paper, we introduce 2DGS-Room, a novel method leveraging 2D Gaussian Splatting for high-fidelity indoor scene reconstruction. Specifically, we employ a seed-guided mechanism to control the distribution of 2D Gaussians, with the density of seed points dynamically optimized through adaptive growth and pruning mechanisms.

简述了2DGS Room 这篇paper： 2DGS-Room: Seed-Guided 2D Gaussian Splatting with Geometric Constrains for High-Fidelity Indoor Scene Reconstruction Contributions: • We propose 2DGS-Room, a novel method for indoor scene reconstruction based on 2DGS, which leverages the seed points maintaining the scene structure to guide the distribution ...

2024年11月9日 · Normal Consistency: 2DGS这种基于2D Gaussians的surfels表达需要在局部上保证和真实的表面对齐，但体渲染中一条光线上可能会有多个半透明的surfels，于是2DGS将中间的surfels即累积不透明度为0.5的点视为真实表面所在的位置。

2021年9月1日 · A small seed can make a big difference in two-dimensional (2D) crystal growth. Recently in Science, Xu et al. developed a seed transfected epitaxy growth strategy for synthesizing single-crystalline 2H molybdenum ditelluride (MoTe 2) wafers with high quality and electrical performance.

Compute the differential entropy of the multivariate normal. Fit a multivariate normal distribution to data.

2014年11月17日 · I'm looking for a two-dimensional analog to the numpy.random.normal routine, i.e. numpy.random.normal generates a one-dimensional array with a mean, standard deviation and sample number as input, and what I'm looking for is a way to generate points in two-dimensional space with those same input parameters.

In this paper, we introduce 2DGS-Room, a novel method leveraging 2D Gaussian Splatting for high-fidelity indoor scene reconstruction. Specifically, we employ a seed-guided mechanism to control the distribution of 2D Gaussians, with the density of seed points dynamically optimized through adaptive growth and pruning mechanisms.

numpy.random.normal# random. normal (loc = 0.0, scale = 1.0, size = None) # Draw random samples from a normal (Gaussian) distribution.

2018年2月1日 · w2 = tf.random_normal([3,1], stddev=1, seed=1) ... 我们知道 tf.random_normal 方法是生成随机的矩阵参数，如上例中就是生成一个3×1的矩阵， stddev 参数是控制方差，这些都好理解，就是看到这个 seed 参数的时候有点懵，下面截取的是官方 API 的解释： seed: A Python integer. Used to create a random seed for the distribution. See tf.set_random_seed for behavior. 我查阅了一些博客，基本上都是对这段官文的翻译，请原谅我看了翻译依然没搞懂。 再回到 …