457 research outputs found
A 2D hybrid method for interfacial transport of passive scalars
A hybrid Eulerian-Lagrangian method is proposed to simulate passive scalar
transport on arbitrary shape interface. In this method, interface deformation
is tracked by an Eulerian method while the transport of the passive scalar on
the material interface is solved by a single-layer Lagrangian particle method.
To avoid particle clustering, a novel remeshing approach is proposed. This
remeshing method can resample particles, adjust the position of particles by a
relaxation process, and transfer mass from pre-existing particles to resampled
particles via a redistribution process, which preserves mass both globally and
locally. Computational costs are controlled by an adaptive remeshing strategy.
Accuracy is assessed by a series of test cases.Comment: 32 pages 1nd 14 figure
DiffRoom: Diffusion-based High-Quality 3D Room Reconstruction and Generation
We present DiffRoom, a novel framework for tackling the problem of
high-quality 3D indoor room reconstruction and generation, both of which are
challenging due to the complexity and diversity of the room geometry. Although
diffusion-based generative models have previously demonstrated impressive
performance in image generation and object-level 3D generation, they have not
yet been applied to room-level 3D generation due to their computationally
intensive costs. In DiffRoom, we propose a sparse 3D diffusion network that is
efficient and possesses strong generative performance for Truncated Signed
Distance Field (TSDF), based on a rough occupancy prior. Inspired by
KinectFusion's incremental alignment and fusion of local SDFs, we propose a
diffusion-based TSDF fusion approach that iteratively diffuses and fuses TSDFs,
facilitating the reconstruction and generation of an entire room environment.
Additionally, to ease training, we introduce a curriculum diffusion learning
paradigm that speeds up the training convergence process and enables
high-quality reconstruction. According to the user study, the mesh quality
generated by our DiffRoom can even outperform the ground truth mesh provided by
ScanNet
Perception Imitation: Towards Synthesis-free Simulator for Autonomous Vehicles
We propose a perception imitation method to simulate results of a certain
perception model, and discuss a new heuristic route of autonomous driving
simulator without data synthesis. The motivation is that original sensor data
is not always necessary for tasks such as planning and control when semantic
perception results are ready, so that simulating perception directly is more
economic and efficient. In this work, a series of evaluation methods such as
matching metric and performance of downstream task are exploited to examine the
simulation quality. Experiments show that our method is effective to model the
behavior of learning-based perception model, and can be further applied in the
proposed simulation route smoothly
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