Person Re-identification: Past, Present and Future

Person re-identification (re-ID) has become increasingly popular in the community due to its application and research significance. It aims at spotting a person of interest in other cameras. In the early days, hand-crafted algorithms and small-scale evaluation were predominantly reported. Recent years have witnessed the emergence of large-scale datasets and deep learning systems which make use of large data volumes. Considering different tasks, we classify most current re-ID methods into two classes, i.e., image-based and video-based; in both tasks, hand-crafted and deep learning systems will be reviewed. Moreover, two new re-ID tasks which are much closer to real-world applications are described and discussed, i.e., end-to-end re-ID and fast re-ID in very large galleries. This paper: 1) introduces the history of person re-ID and its relationship with image classification and instance retrieval; 2) surveys a broad selection of the hand-crafted systems and the large-scale methods in both image- and video-based re-ID; 3) describes critical future directions in end-to-end re-ID and fast retrieval in large galleries; and 4) finally briefs some important yet under-developed issues

Improved estimates of 222 nm far-UVC susceptibility for aerosolized human coronavirus via a validated high-fidelity coupled radiation-CFD code.

Transmission of SARS-CoV-2 by aerosols has played a significant role in the rapid spread of COVID-19 across the globe. Indoor environments with inadequate ventilation pose a serious infection risk. Whilst vaccines suppress transmission, they are not 100% effective and the risk from variants and new viruses always remains. Consequently, many efforts have focused on ways to disinfect air. One such method involves use of minimally hazardous 222 nm far-UVC light. Whilst a small number of controlled experimental studies have been conducted, determining the efficacy of this approach is difficult because chamber or room geometry, and the air flow within them, influences both far-UVC illumination and aerosol dwell times. Fortunately, computational multiphysics modelling allows the inadequacy of dose-averaged assessment of viral inactivation to be overcome in these complex situations. This article presents the first validation of the WYVERN radiation-CFD code for far-UVC air-disinfection against survival fraction measurements, and the first measurement-informed modelling approach to estimating far-UVC susceptibility of viruses in air. As well as demonstrating the reliability of the code, at circa 70% higher, our findings indicate that aerosolized human coronaviruses are significantly more susceptible to far-UVC than previously thought

Exploring semantic inter-class relationships (SIR) for zero-shot action recognition

© Copyright 2015, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved. Automatically recognizing a large number of action categories from videos is of significant importance for video understanding. Most existing works focused on the design of more discriminative feature representation, and have achieved promising results when the positive samples are enough. However, very limited efforts were spent on recognizing a novel action without any positive exemplars, which is often the case in the real settings due to the large amount of action classes and the users' queries dramatic variations. To address this issue, we propose to perform action recognition when no positive exemplars of that class are provided, which is often known as the zero-shot learning. Different from other zero-shot learning approaches, which exploit attributes as the intermediate layer for the knowledge transfer, our main contribution is SIR, which directly leverages the semantic inter-class relationships between the known and unknown actions followed by label transfer learning. The inter-class semantic relationships are automatically measured by continuous word vectors, which learned by the skip-gram model using the large-scale text corpus. Extensive experiments on the UCF101 dataset validate the superiority of our method over fully-supervised approaches using few positive exemplars

Viral video style: A closer look at viral videos on YouTube

Viral videos that gain popularity through the process of Internet sharing are having a profound impact on society. Existing studies on viral videos have only been on small or confidential datasets. We collect by far the largest open benchmark for viral video study called CMU Viral Video Dataset, and share it with researchers from both academia and industry. Having verified existing observations on the dataset, we discover some interesting characteristics of viral videos. Based on our analysis, in the second half of the paper, we propose a model to forecast the future peak day of viral videos. The application of our work is not only important for advertising agencies to plan advertising campaigns and estimate costs, but also for companies to be able to quickly respond to rivals in viral marketing campaigns. The proposed method is unique in that it is the first attempt to incorporate video metadata into the peak day prediction. The empirical results demonstrate that the proposed method outperforms the state-of-the-art methods, with statistically significant differences. Copyright 2014 ACM

Dynamic concept composition for zero-example event detection

© Copyright 2016, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved. In this paper, we focus on automatically detecting events in unconstrained videos without the use of any visual training exemplars. In principle, zero-shot learning makes it possible to train an event detection model based on the assumption that events (e.g. birthday party) can be described by multiple mid-level semantic concepts (e.g. "blowing candle", "birthday cake"). Towards this goal, we first pre-Train a bundle of concept classifiers using data from other sources. Then we evaluate the semantic correlation of each concept w.r.t. the event of interest and pick up the relevant concept classifiers, which are applied on all test videos to get multiple prediction score vectors. While most existing systems combine the predictions of the concept classifiers with fixed weights, we propose to learn the optimal weights of the concept classifiers for each testing video by exploring a set of online available videos with freeform text descriptions of their content. To validate the effectiveness of the proposed approach, we have conducted extensive experiments on the latest TRECVID MEDTest 2014, MEDTest 2013 and CCV dataset. The experimental results confirm the superiority of the proposed approach

QCD Approach to B->D \pi Decays and CP Violation

The branching ratios and CP violations of the $B\to D\pi$ decays, including both the color-allowed and the color-suppressed modes, are investigated in detail within QCD framework by considering all diagrams which lead to three effective currents of two quarks. An intrinsic mass scale as a dynamical gluon mass is introduced to treat the infrared divergence caused by the soft collinear approximation in the endpoint regions, and the Cutkosky rule is adopted to deal with a physical-region singularity of the on mass-shell quark propagators. When the dynamical gluon mass $\mu_g$ is regarded as a universal scale, it is extracted to be around $\mu_g = 440$ MeV from one of the well-measured $B\to D\pi$ decay modes. The resulting predictions for all branching ratios are in agreement with the current experimental measurements. As these decays have no penguin contributions, there are no direct $CP$ asymmetries. Due to interference between the Cabibbo-suppressed and the Cabibbo-favored amplitudes, mixing-induced CP violations are predicted in the $B\to D^{\pm}\pi^{\mp}$ decays to be consistent with the experimental data at 1-$\sigma$ level. More precise measurements will be helpful to extract weak angle $2\beta+\gamma$.Comment: 21pages,5 figures,3 tables, typos corrected and numerical result for one of decay channels is improve

Determinant representations of scalar products for the open XXZ chain with non-diagonal boundary terms

With the help of the F-basis provided by the Drinfeld twist or factorizing F-matrix for the open XXZ spin chain with non-diagonal boundary terms, we obtain the determinant representations of the scalar products of Bethe states of the model.Comment: Latex file, 28 pages, based on the talk given by W. -L. Yang at Statphys 24, Cairns, Australia, 19-23 July, 201

Exploration of a potent PI3 kinase/mTOR inhibitor as a novel anti-fibrotic agent in IPF

© 2016 BMJ Publishing Group Ltd & British Thoracic Society.Rationale Idiopathic pulmonary fibrosis (IPF) is the most rapidly progressive and fatal of all fibrotic conditions with no curative therapies. Common pathomechanisms between IPF and cancer are increasingly recognised, including dysfunctional pan-PI3 kinase (PI3K) signalling as a driver of aberrant proliferative responses. GSK2126458 is a novel, potent, PI3K/mammalian target of rapamycin (mTOR) inhibitor which has recently completed phase I trials in the oncology setting. Our aim was to establish a scientific and dosing framework for PI3K inhibition with this agent in IPF at a clinically developable dose. Methods We explored evidence for pathway signalling in IPF lung tissue and examined the potency of GSK2126458 in fibroblast functional assays and precision-cut IPF lung tissue. We further explored the potential of IPF patient-derived bronchoalveolar lavage (BAL) cells to serve as pharmacodynamic biosensors to monitor GSK2126458 target engagement within the lung. Results We provide evidence for PI3K pathway activation in fibrotic foci, the cardinal lesions in IPF. GSK2126458 inhibited PI3K signalling and functional responses in IPF-derived lung fibroblasts, inhibiting Akt phosphorylation in IPF lung tissue and BAL derived cells with comparable potency. Integration of these data with GSK2126458 pharmacokinetic data from clinical trials in cancer enabled modelling of an optimal dosing regimen for patients with IPF. Conclusions Our data define PI3K as a promising therapeutic target in IPF and provide a scientific and dosing framework for progressing GSK2126458 to clinical testing in this disease setting. A proof-ofmechanism trial of this agent is currently underway. Trial registration number NCT01725139, pre-clinical

Operator entanglement of two-qubit joint unitary operations revisited: Schmidt number approach

Operator entanglement of two-qubit joint unitary operations is revisited. Schmidt number is an important attribute of a two-qubit unitary operation, and may have connection with the entanglement measure of the unitary operator. We found the entanglement measure of two-qubit unitary operators is classified by the Schmidt number of the unitary operators. The exact relation between the operator entanglement and the parameters of the unitary operator is clarified too.Comment: To appear in the Brazilian Journal of Physic

Addressing Security Properties in Systems of Systems: Challenges and Ideas

Within growing pervasive information systems, Systems of Systems (SoS) emerge as a new research frontier. A SoS is formed by a set of constituent systems that live on their own with well-established functionalities and requirements, and, in certain circumstances, they must collaborate to achieve a common mission. In this scenario, security is one crucial property that needs to be considered since the early stages of SoS lifecycle. Unfortunately, SoS security cannot be guaranteed by addressing the security of each constituent system separately. The aim of this paper is to discuss the challenges faced in addressing the security of SoS and to propose some research ideas centered around the notion of a mission to be carried out by the SoS.Ministerio dell'Universitá e della Ricerca (Italia) GAUSS 2015KWREMXMinisterio de Economía y Competitividad TIN2016-76956-C3-2-R (POLOLAS