feature maps; and the multi-view multi-scale early fusion model favors that features aligned to the same ground-plane point have consistent scales. We test our 3 fusion models on 3 multi-view counting datasets, PETS2009, DukeMTMC, and a newly collected multi-view counting dataset containing a...
0. 论文信息 标题:CityGaussianV2: Efficient and Geometrically Accurate Reconstruction for Large-Scale Scenes 作者:Yang Liu, Chuanchen Luo, Zhongkai Mao, Junran Peng, Zhaoxiang Zhang 机构:NLPR, MAIS, Institute of Automation, Chinese Academy of Sciences、University of Chinese Academy of Sciences、Centre...
经过reshape和permute后,同样分解为多头注意力的形式 (2, 228, 16, 24, 16)。 计算新的注意力矩阵:t_attn = (t_q @ t_k.transpose(-2, -1)) * self.scale,经过softmax和dropout得到最终的注意力权重。 利用t_attn @ t_v得到加权后的输出t_x,恢复维度后为 (2, 24, 228, 256),再与tc_x相加...
论文标题: CityGaussian: Real-time High-quality Large-Scale Scene Rendering with Gaussians 论文链接: https://arxiv.org/pdf/2404.01133 项目网站: https://dekuliutesla.github.io/citygs/ 一、方法总览 我们提出的CityGaussian算法,它基于3D Gaussian Splatting(3DGS)技术,针对大规模场景的重建提出了一种高...
CityGaussianV2填补了大规模场景下几何评测协议长期以来的空白,在Tanks and Temple (TnT) 数据集的启发下,基于点云的目击频次统计设计了针对大规模场景欠观测区域的边界估计方案。具体而言,点云真值会首先被初始化为3DGS,在遍历所有训练视图的同时记录每个点的观测频次,观测频次低于阈值的点将被滤除;剩余的点将用于估计...
这些标注是通过将从 OSM 数据集生成的 3D 城市布局投影至图像上生成的。这种方式可以很容易地将标注数据扩展至世界上的其他城市。 方法 CityDreamer 将 3D 城市生成分解为 4 步:无边界城市布局生成、城市背景生成、建筑实例生成和图像融合。 无边界城市布局生成...
这些标注是通过将从 OSM 数据集生成的 3D 城市布局投影至图像上生成的。这种方式可以很容易地将标注数据扩展至世界上的其他城市。 方法 CityDreamer 将 3D 城市生成分解为 4 步:无边界城市布局生成、城市背景生成、建筑实例生成和图像融合。 无边界城市布局生成...
为了使生成的城市在布局上和外观上都更逼真,研究人员们构建了 2 个数据集:OSM 和 GoogleEarth。前者从 OpenStreetMap [1] 提取了超过 80 个知名城市、超过 6000km2 的俯视视角的高度图和语义分割图;后者从 Google Earth Studio [2] 上提取了美国纽约市的 400 环形轨迹,包含 24,000 张图像及对应的语义分割...
intensity effect is a strong measure for controlling the growth of CO 2 emissions in the eastern region. However, the contribution of the scale effect to CO 2 emissions is more pronounced in the western region. In addition, we found that the desirable output productivity effects had a ...
Scene understanding of full-scale 3D models of an urban area remains a challenging task. While advanced computer vision techniques offer cost-effective approaches to analyse 3D urban elements, a precise and densely labelled dataset is quintessential. The paper presents the first-ever labelled dataset ...