Text-based Localization of Moments in a Video Corpus

Prior works on text-based video moment localization focus on temporally grounding the textual query in an untrimmed video. These works assume that the relevant video is already known and attempt to localize the moment on that relevant video only. Different from such works, we relax this assumption and address the task of localizing moments in a corpus of videos for a given sentence query. This task poses a unique challenge as the system is required to perform: (i) retrieval of the relevant video where only a segment of the video corresponds with the queried sentence, and (ii) temporal localization of moment in the relevant video based on sentence query. Towards overcoming this challenge, we propose Hierarchical Moment Alignment Network (HMAN) which learns an effective joint embedding space for moments and sentences. In addition to learning subtle differences between intra-video moments, HMAN focuses on distinguishing inter-video global semantic concepts based on sentence queries. Qualitative and quantitative results on three benchmark text-based video moment retrieval datasets - Charades-STA, DiDeMo, and ActivityNet Captions - demonstrate that our method achieves promising performance on the proposed task of temporal localization of moments in a corpus of videos

Solution-processable silicon phthalocyanines in electroluminescent and photovoltaic devices

E.Z.-C. acknowledges the University of St. Andrews for financial support. The authors thank the EPSRC UK National Mass Spectrometry Facility at Swansea University for analytical services. I.D.W.S. acknowledges support from the EPSRC (grant EP/J01771X), the European Research Council (grant 321305), and a Royal Society Wolfson Research Merit Award.Phthalocyanines and their main group and metal complexes are important classes of organic semiconductor materials, but are usually highly insoluble so frequently need to be processed by vacuum deposition in devices. We report two highly soluble silicon phthalocyanine (SiPc) diester compounds and demonstrate their potential as organic semiconductor materials. Near-infrared (λEL = 698-709 nm) solution-processed organic light- emitting diodes (OLEDs) were fabricated and exhibited external quantum efficiencies (EQEs) of up to 1.4%. Binary bulk heterojunction solar cells employing P3HT or PTB7 as the donor and the SiPc as the acceptor provided power conversion efficiencies (PCE) of up to 2.7% under simulated solar illumination. Our results show that soluble SiPcs are promising materials for organic electronics.Publisher PDFPeer reviewe

Tuning crystalline ordering by annealing and additives to study its effect on exciton diffusion in a polyalkylthiophene copolymer

M.C, M.T.S, A.R and I.D.W.S acknowledge support from the European Research Council (EXCITON grant 321305). I.D.W.S acknowledges Royal Society Wolfson Research Merit Award. Use of the Stanford Synchrotron Radiation Lightsource, SLAC National Accelerator Laboratory, is supported by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences under Contract No. DE-AC02-76SF00515The influence of various processing conditions on the singlet exciton diffusion is explored in films of a conjugated random copolymer poly-(3-hexylthiophene-co-3-dodecylthiophene) (P3HT-co-P3DDT) and correlated with the degree of crystallinity probed by grazing incidence X-ray scattering and with exciton bandwidth determined from absorption spectra. The exciton diffusion coefficient is deduced from exciton-exciton annihilation measurements and is found to increase by more than a factor of three when thin films are annealed using CS2 solvent vapour. A doubling of exciton diffusion coefficient is observed upon melt annealing at 200 °C and the corresponding films show about 50% enhancement in the degree of crystallinity. In contrast, films fabricated from polymer solutions containing a small amount of either solvent additive or nucleating agent show a decrease in exciton diffusion coefficient possibly due to formation of traps for excitons. Our results suggest that the enhancement of exciton diffusivity occurs because of increased crystallinity of alkyl-stacking and longer conjugation of aggregated chains which reduces the exciton bandwidth.Publisher PDFPeer reviewe

RGB2LIDAR: Towards Solving Large-Scale Cross-Modal Visual Localization

We study an important, yet largely unexplored problem of large-scale cross-modal visual localization by matching ground RGB images to a geo-referenced aerial LIDAR 3D point cloud (rendered as depth images). Prior works were demonstrated on small datasets and did not lend themselves to scaling up for large-scale applications. To enable large-scale evaluation, we introduce a new dataset containing over 550K pairs (covering 143 km^2 area) of RGB and aerial LIDAR depth images. We propose a novel joint embedding based method that effectively combines the appearance and semantic cues from both modalities to handle drastic cross-modal variations. Experiments on the proposed dataset show that our model achieves a strong result of a median rank of 5 in matching across a large test set of 50K location pairs collected from a 14km^2 area. This represents a significant advancement over prior works in performance and scale. We conclude with qualitative results to highlight the challenging nature of this task and the benefits of the proposed model. Our work provides a foundation for further research in cross-modal visual localization.Comment: ACM Multimedia 202

Engineered exciton diffusion length enhances device efficiency in small molecule photovoltaics

n organic photovoltaic blends, there is a trade-off between exciton harvesting and charge extraction because of the short exciton diffusion length. Developing a way of increasing exciton diffusion length would overcome this trade-off by enabling efficient light harvesting from large domains. In this work, we engineered (enhanced) both exciton diffusion length and domain size using solvent vapour annealing (SVA). We show that SVA can give a three-fold enhancement in exciton diffusion coefficient (D) and nearly a doubling of exciton diffusion length. It also increases the domain size, leading to enhancement of charge extraction efficiency from 63 to 89%. Usually larger domains would reduce exciton harvesting but this is overcome by the large increase in exciton diffusion, leading to a 20% enhancement in device efficiency

Cross-View Visual Geo-Localization for Outdoor Augmented Reality

Precise estimation of global orientation and location is critical to ensure a compelling outdoor Augmented Reality (AR) experience. We address the problem of geo-pose estimation by cross-view matching of query ground images to a geo-referenced aerial satellite image database. Recently, neural network-based methods have shown state-of-the-art performance in cross-view matching. However, most of the prior works focus only on location estimation, ignoring orientation, which cannot meet the requirements in outdoor AR applications. We propose a new transformer neural network-based model and a modified triplet ranking loss for joint location and orientation estimation. Experiments on several benchmark cross-view geo-localization datasets show that our model achieves state-of-the-art performance. Furthermore, we present an approach to extend the single image query-based geo-localization approach by utilizing temporal information from a navigation pipeline for robust continuous geo-localization. Experimentation on several large-scale real-world video sequences demonstrates that our approach enables high-precision and stable AR insertion.Comment: IEEE VR 202