本文对采用RGBD Fusion类的传统三维人体重建的三个算法流程,即self 3D Self-Portraits[1],DoubleFusion[2],PIFuFusion[3],做个简单的记录,不涉及细节,感兴趣的读者可自行阅读原始论文。 一.简介 场景均为相机固定人体转动,也就是算法的输入为多视角下的人体RGBD图,核心在于配准算法。 二.具体流程 1.3D Self-Por...
相比于KinectFusion,DynamicFusion【1】最大的区别在于引入了Deformation Graph【2】,通过Warp field(包括对应于相机运动的刚性变换,和对应于物体形变的非刚性变换)将canonicial空间的model变换到camera空间的frame,从而实现对待重建的动态物体的tsdf场进行更新,最终完成重建。下文着重对与KinectFusion不同的部分做下描述。
RGBD-Fusion: Depth Refinement for Diffuse and Specular ObjectsThe popularity of low-cost RGB-D scanners is increasing on a daily basis and has set off a major boost in 3D computer vision research. Nevertheless, commodity scanners often cannot capture subtle details in the environment. In other ...
An Efficient Monocular Depth Prediction Network Using Coordinate Attention and Feature Fusion The recovery of reasonable depth information from different scenes is a popular topic in the field of computer vision. For generating depth maps with better details, we present an efficacious monocular depth pre...
RGBDFusion.simplify_mesh( mesh=mesh, voxel_size=0.05, save=args.mesh save=args.mesh, decimation=args.smp_decimation, voxel_size=args.smp_voxel_length, smooth_iter=args.smooth_iter ) 62 changes: 39 additions & 23 deletions 62 modules/fusion.py Original file line numberDiff line numberDiff...
笔者在调查中发现,实时三元重建系统的重要研究方向主要是Fusion系列。由于摄像机的姿势估计通常会出现错误,因此,为了生成与真实对象一致的点云图像而叠加多个图像的点云时,这种方法也可能会出现故障或失真。为了避免连续积累的误差,最终实现更好的3D重建模型,笔者得知可以利用捆绑调整(BA:Bundle ...
EFF:高效特征融合模块,适用于图像分割任务,2d和3d版本 3400 1 00:50 App FECAM:频率增强通道注意力模块,适用于时间序列预测任务,可以缝合在transformer中,即插即用 4043 0 00:52 App TPAMI 2024 | 有效涨点的特征融合模块FreqFusion,目标检测、图像分割等任务均适用 1786 0 00:34 App MDCR:多膨胀率通道...
基于深度融合的RGBD显著目标检测 此文为07-ECCV-Accurate RGB-D Salient Object Detection via Collaborative Learning中所注明的RGB-D首例研究,故在此全文翻译。 摘要:RGBD显著性检测设计了各种低水平的显著性线索,如颜色和
PDF:X-Section: Cross-Section Prediction for Enhanced RGBD Fusion Abstract Detailed 3D reconstruction is an important challenge with application to robotics, augmented and virtual reality, which has seen impressive progress throughout the past years. Advancements were driven by the availability of depth ...
Offical implementation of paper "MSAF: Multimodal Split Attention Fusion" pytorchaction-recognitionmultimodal-learningmultimodal-sentiment-analysismultimodal-deep-learningntu-rgbdcmu-moseimultimodal-emotion-recognitionravdess UpdatedJun 16, 2021 Python itskalvik/ST-GCN ...