3D-BEVIS: Bird's-Eye-View Instance Segmentation

Recent deep learning models achieve impressive results on 3D scene analysis tasks by operating directly on unstructured point clouds. A lot of progress was made in the field of object classification and semantic segmentation. However, the task of instance segmentation is less explored. In this work, we present 3D-BEVIS, a deep learning framework for 3D semantic instance segmentation on point clouds. Following the idea of previous proposal-free instance segmentation approaches, our model learns a feature embedding and groups the obtained feature space into semantic instances. Current point-based methods scale linearly with the number of points by processing local sub-parts of a scene individually. However, to perform instance segmentation by clustering, globally consistent features are required. Therefore, we propose to combine local point geometry with global context information from an intermediate bird's-eye view representation.Comment: camera-ready version for GCPR '1

Analytical and numerical studies of central galactic outflows powered by tidal disruption events -- a model for the Fermi bubbles?

Capture and tidal disruption of stars by the supermassive black hole in the Galactic center (GC) should occur regularly. The energy released and dissipated by this processes will affect both the ambient environment of the GC and the Galactic halo. A single star of super-Eddington eruption generates a subsonic out ow with an energy release of more than $10^{52}$ erg, which still is not high enough to push shock heated gas into the halo. Only routine tidal disruption of stars near the GC can provide enough cumulative energy to form and maintain large scale structures like the Fermi Bubbles. The average rate of disruption events is expected to be $10^{-4}$ ~ $10^{-5}$ yr$^{-1}$, providing the average power of energy release from the GC into the halo of dW/dt ~ 3*10$^{41}$ erg/s, which is needed to support the Fermi Bubbles. The GC black hole is surrounded by molecular clouds in the disk, but their overall mass and filling factor is too low to stall the shocks from tidal disruption events significantly. The de facto continuous energy injection on timescales of Myr will lead to the propagation of strong shocks in a density stratified Galactic halo and thus create elongated bubble-like features, which are symmetric to the Galactic midplane.Comment: 11 pages, 5 figures. The title and abstract have been changed. Accepted by Astrophysical Journa

Radiative decay of the dynamically generated open and hidden charm scalar meson resonances D_{s0}^*(2317) and X(3700)

We present the formalism for the decay of dynamically generated scalar mesons with open- or hidden-charm and give results for the decay of D^*_{s0} (2317) to \gamma D_s^* plus that of a hidden charm scalar meson state predicted by the theory around 3700 MeV decaying into \gamma J/\psi.Comment: Appendix adde

{DAFormer}: {I}mproving Network Architectures and Training Strategies for Domain-Adaptive Semantic Segmentation

As acquiring pixel-wise annotations of real-world images for semantic segmentation is a costly process, a model can instead be trained with more accessible synthetic data and adapted to real images without requiring their annotations. This process is studied in unsupervised domain adaptation (UDA). Even though a large number of methods propose new adaptation strategies, they are mostly based on outdated network architectures. As the influence of recent network architectures has not been systematically studied, we first benchmark different network architectures for UDA and then propose a novel UDA method, DAFormer, based on the benchmark results. The DAFormer network consists of a Transformer encoder and a multi-level context-aware feature fusion decoder. It is enabled by three simple but crucial training strategies to stabilize the training and to avoid overfitting DAFormer to the source domain: While the Rare Class Sampling on the source domain improves the quality of pseudo-labels by mitigating the confirmation bias of self-training towards common classes, the Thing-Class ImageNet Feature Distance and a learning rate warmup promote feature transfer from ImageNet pretraining. DAFormer significantly improves the state-of-the-art performance by 10.8 mIoU for GTA->Cityscapes and 5.4 mIoU for Synthia->Cityscapes and enables learning even difficult classes such as train, bus, and truck well. The implementation is available at https://github.com/lhoyer/DAFormer

The effect of interactions between a bacterial strain isolated from drinking water and a pathogen surrogate on biofilms formation diverged under static vs flow conditions

AimsInteractions with water bacteria affect the incorporation of pathogens into biofilms and thus pathogen control in drinking water systems. This study was to examine the impact of static vs flow conditions on interactions between a pathogen and a water bacterium on pathogen biofilm formation under laboratory settings.Methods and ResultsA pathogen surrogate Escherichia coli and a drinking water isolate Stenotrophomonas maltophilia was selected for this study. Biofilm growth was examined under two distinct conditions, in flow cells with continuous medium supply vs in static microtitre plates with batch culture. E. coli biofilm was greatly stimulated (c. 2–1000 times faster) with the presence of S. maltophilia in flow cells, but surprisingly inhibited (c. 65–95% less biomass) in microtitre plates. These divergent effects were explained through various aspects including surface attachment, cellular growth, extracellular signals and autoaggregation.ConclusionsInteractions with the same water bacterium resulted in different effects on E. coli biofilm formation when culture conditions changed from static to flow.Significance and Impact of StudyThis study highlights the complexity of species interactions on biofilm formation and suggests that environmental conditions such as the flow regime can be taken into consideration for the management of microbial contamination in drinking water systems.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/140002/1/jam13596.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/140002/2/jam13596_am.pd

Modeling the Optical Afterglow of GRB 030329

The best-sampled afterglow light curves are available for GRB 030329. A distinguishing feature of this event is the obvious rebrightening at around 1.6 days after the burst. Proposed explanations for the rebrightening mainly include the two-component jet model and the refreshed shock model, although a sudden density-jump in the circumburst environment is also a potential choice. Here we re-examine the optical afterglow of GRB 030329 numerically in light of the three models. In the density-jump model, no obvious rebrightening can be produced at the jump moment. Additionally, after the density jump, the predicted flux density decreases rapidly to a level that is significantly below observations. A simple density-jump model thus can be excluded. In the two-component jet model, although the observed late afterglow (after 1.6 days) can potentially be explained as emission from the wide-component, the emergence of this emission actually is too slow and it does not manifest as a rebrightening as previously expected. The energy-injection model seems to be the most preferred choice. By engaging a sequence of energy-injection events, it provides an acceptable fit to the rebrightening at $\sim 1.6$ d, as well as the whole observed light curve that extends to $\sim 80$ d. Further studies on these multiple energy-injection processes may provide a valuable insight into the nature of the central engines of gamma-ray bursts.Comment: 18 pages, 3 figures; a few references added and minor word changes; now accepted for publication in Ap

Quasi-Homogeneous Backward-Wave Plasmonic Structures: Theory and Accurate Simulation

Backward waves and negative refraction are shown to exist in plasmonic crystals whose lattice cell size is a very small fraction of the vacuum wavelength (less than 1/40th in an illustrative example). Such ``quasi-homogeneity'' is important, in particular, for high-resolution imaging. Real and complex Bloch bands are computed using the recently developed finite-difference calculus of ``Flexible Local Approximation MEthods'' (FLAME) that produces linear eigenproblems, as opposed to quadratic or nonlinear ones typical for other techniques. FLAME dramatically improves the accuracy by incorporating local analytical approximations of the solution into the numerical scheme.Comment: 4 pages, 3 figure