論文紹介:Grad-CAM: Visual explanations from deep networks via gradient-based loca...Kazuki Adachi
?
Selvaraju, Ramprasaath R., et al. "Grad-cam: Visual explanations from deep networks via gradient-based localization." The IEEE International Conference on Computer Vision (ICCV), 2017, pp. 618-626
This document introduces ggplot2, an R package for creating graphs and plots. It discusses the core components of ggplot2 including ggplot() for initializing plots, geom for geometries like points and lines, stat for statistical transformations, and opts for setting plot options. It provides examples using the mtcars dataset to demonstrate how to create scatter plots and add regression lines using the grammar of graphics of ggplot2.
DynamicFusion is a method for reconstructing and tracking non-rigid scenes in real-time by extending KinectFusion. It uses a volumetric truncated signed distance function (TSDF) to integrate depth maps from multiple viewpoints into a global reconstruction. Live depth frames are aligned to a dense surface prediction generated by raycasting the TSDF. This closes the loop between mapping and localization for tracking dynamic, non-rigid scenes.
DynamicFusion is a method for reconstructing and tracking non-rigid scenes in real-time by extending KinectFusion. It uses a volumetric truncated signed distance function (TSDF) to integrate depth maps from multiple viewpoints into a global reconstruction. Live depth frames are aligned to a dense surface prediction generated by raycasting the TSDF. This closes the loop between mapping and localization for tracking dynamic, non-rigid scenes.