Online Domain Adaptation for Multi-Object Tracking

Automatically detecting, labeling, and tracking objects in videos depends first and foremost on accurate category-level object detectors. These might, however, not always be available in practice, as acquiring high-quality large scale labeled training datasets is either too costly or impractical for all possible real-world application scenarios. A scalable solution consists in re-using object detectors pre-trained on generic datasets. This work is the first to investigate the problem of on-line domain adaptation of object detectors for causal multi-object tracking (MOT). We propose to alleviate the dataset bias by adapting detectors from category to instances, and back: (i) we jointly learn all target models by adapting them from the pre-trained one, and (ii) we also adapt the pre-trained model on-line. We introduce an on-line multi-task learning algorithm to efficiently share parameters and reduce drift, while gradually improving recall. Our approach is applicable to any linear object detector, and we evaluate both cheap "mini-Fisher Vectors" and expensive "off-the-shelf" ConvNet features. We quantitatively measure the benefit of our domain adaptation strategy on the KITTI tracking benchmark and on a new dataset (PASCAL-to-KITTI) we introduce to study the domain mismatch problem in MOT.Comment: To appear at BMVC 201

The localization transition in SU(3) gauge theory

We study the Anderson-like localization transition in the spectrum of the Dirac operator of quenched QCD. Above the deconfining transition we determine the temperature dependence of the mobility edge separating localized and delocalized eigenmodes in the spectrum. We show that the temperature where the mobility edge vanishes and localized modes disappear from the spectrum, coincides with the critical temperature of the deconfining transition. We also identify topological charge related close to zero modes in the Dirac spectrum and show that they account for only a small fraction of localized modes, a fraction that is rapidly falling as the temperature increases.Comment: 7 pages, 5 figures, v3: additional data on finer lattice; final, published versio

Temperature-resolution anomalies in the reconstruction of time dynamics from energy-loss experiments

Inelastic scattering techniques provide a powerful approach to studying electron and nuclear dynamics, via reconstruction of a propagator that quantifies the time evolution of a system. There is now growing interest in applying such methods to very low energy excitations, such as lattice vibrations, but in this limit the cross section is no longer proportional to a propagator. Significant deviations occur due to the finite temperature Bose statistics of the excitations. Here we consider this issue in the context of high-resolution electron energy loss experiments on the copper-oxide superconductor Bi$_2$Sr$_2$CaCu$_2$O$_{8+x}$. We find that simple division of a Bose factor yields an accurate propagator on energy scales greater than the resolution width. However, at low energy scales, the effects of resolution and finite temperature conspire to create anomalies in the dynamics at long times. We compare two practical ways for dealing with such anomalies, and discuss the range of validity of the technique in light of this comparison.Comment: 19 pages, 2 figures, submitted to Journal of Physics

Experience of communal conflicts and inter-group lending

We provide micro economic evidence on the link between ethnic frictions and market efficiency, using dyadic data on managers and borrowers from a large Indian bank. Our analysis builds on the idea that exposure to religion-based communal violence may intensify branch managers’ same-group preferences, and thus result in lending decisions that are more sensitive to a borrower’s religion. We find that,in our sample of Hindu loan officers, those with substantial riot exposure prior to joining the bank lend relatively less to Muslim borrowers. Riot-exposed officers’ loans to Muslims are also less likely to default, suggesting that the lower lending rate for Muslims is driven by taste-based discrimination. This bias is persistent across a bank officer’s tenure, suggesting that the economic costs of ethnic conflict are long-lasting, potentially spanning across generations.https://sites.bu.edu/fisman/files/2018/12/riot_experience_lending_rf23.pdfFirst author draf