explain this "in this work we proposed the scene diffuser diffusion-based generation optimization and planning in 3D scenes scene diffuser is the first framework that models the 3D scene condition generation with a diffusion model and integrates the generation optimization and planning into a unified framework scene diffuser is a conditional generative model for 3D scene understanding it is applicable to various scene-conditioned 3D tasks we demonstrate this potential by evaluating the scene diffuser on various 3D scene understanding tasks including human pose and motion generation NAME_1's grasp generation path planning for 3D navigation and motion planning for robot arms the abilities of scene aware generation physics-based optimization and goal-oriented planning have been continuously pursued by the field of computer vision graphics and Robotics however first there lacks a powerful conditional generator most previous cvae based methods suffer from the posterior collapse problem ignoring the scene condition and leading to limited generation diversity second there lacks a unified framework that could address existing discrepancies among the generation optimization and planning models to tackle these limitations scene diffuser models planning as trajectory optimization and optimizes the trajectory by sampling trajectory level distribution the modeled scene condition goal-oriented trajectory is formulated as follows we use a conditional diffusion model to generate certain trajectories with the scene condition an Your answer should have exactly 4 paragraphs. Make sure that the last paragraph starts with the word "overall" and that each paragraph is separated by two new lines.
user