Rescaling Egocentric Vision: Collection, Pipeline and Challenges for EPIC-KITCHENS-100

This paper introduces the pipeline to extend the largest dataset in egocentric vision, EPIC-KITCHENS. The effort culminates in EPIC-KITCHENS-100, a collection of 100 hours, 20M frames, 90K actions in 700 variable-length videos, capturing long-term unscripted activities in 45 environments, using head-mounted cameras. Compared to its previous version (Damen in Scaling egocentric vision: ECCV, 2018), EPIC-KITCHENS-100 has been annotated using a novel pipeline that allows denser (54% more actions per minute) and more complete annotations of fine-grained actions (+128% more action segments). This collection enables new challenges such as action detection and evaluating the “test of time”—i.e. whether models trained on data collected in 2018 can generalise to new footage collected two years later. The dataset is aligned with 6 challenges: action recognition (full and weak supervision), action detection, action anticipation, cross-modal retrieval (from captions), as well as unsupervised domain adaptation for action recognition. For each challenge, we define the task, provide baselines and evaluation metrics.Published versionResearch at Bristol is supported by Engineering and Physical Sciences Research Council (EPSRC) Doctoral Training Program (DTP), EPSRC Fellowship UMPIRE (EP/T004991/1). Research at Catania is sponsored by Piano della Ricerca 2016-2018 linea di Intervento 2 of DMI, by MISE - PON I&C 2014-2020, ENIGMA project (CUP: B61B19000520008) and by MIUR AIM - Attrazione e Mobilita Internazionale Linea 1 - AIM1893589 - CUP E64118002540007

A search for the dimuon decay of the Standard Model Higgs boson with the ATLAS detector

A search for the dimuon decay of the Standard Model (SM) Higgs boson is performed using data corresponding to an integrated luminosity of 139 fb(-1) collected with the ATLAS detector in Run 2 pp collisions at root s = 13 TeV at the Large Hadron Collider. The observed (expected) significance over the background-only hypothesis for a Higgs boson with a mass of 125.09 GeV is 2.0 sigma (1.7 sigma). The observed upper limit on the cross section times branching ratio for pp -> H -> mu mu is 2.2 times the SM prediction at 95% confidence level, while the expected limit on a H -> mu mu signal assuming the absence (presence) of a SM signal is 1.1(2.0). The best-fit value of the signal strength parameter, defined as the ratio of the observed signal yield to the one expected in the SM, is mu = 1.2 +/- 0.6. (C) 2020 The Author(s). Published by Elsevier B.V

Measurement of hadronic event shapes in high-p T multijet final states at √s = 13 TeV with the ATLAS detector

A measurement of event-shape variables in proton-proton collisions at large momentum transfer is presented using data collected at s = 13 TeV with the ATLAS detector at the Large Hadron Collider. Six event-shape variables calculated using hadronic jets are studied in inclusive multijet events using data corresponding to an integrated luminosity of 139 fb−1. Measurements are performed in bins of jet multiplicity and in different ranges of the scalar sum of the transverse momenta of the two leading jets, reaching scales beyond 2 TeV. These measurements are compared with predictions from Monte Carlo event generators containing leading-order or next-to-leading order matrix elements matched to parton showers simulated to leading-logarithm accuracy. At low jet multiplicities, shape discrepancies between the measurements and the Monte Carlo predictions are observed. At high jet multiplicities, the shapes are better described but discrepancies in the normalisation are observed. [Figure not available: see fulltext.

Alignment of the ATLAS Inner Detector in Run 2

The performance of the ATLAS Inner Detector alignment has been studied using pp collision data at v s = 13 TeV collected by the ATLAS experiment during Run 2 (2015-2018) of the Large Hadron Collider (LHC). The goal of the detector alignment is to determine the detector geometry as accurately as possible and correct for time-dependent movements. The Inner Detector alignment is based on the minimization of track-hit residuals in a sequence of hierarchical levels, from global mechanical assembly structures to local sensors. Subsequent levels have increasing numbers of degrees of freedom; in total there are almost 750,000. The alignment determines detector geometry on both short and long timescales, where short timescales describe movementswithin anLHCfill. The performance and possible track parameter biases originating from systematic detector deformations are evaluated. Momentum biases are studied using resonances decaying to muons or to electrons. The residual sagitta bias and momentum scale bias after alignment are reduced to less than similar to 0.1 TeV-1 and 0.9 x 10(-3), respectively. Impact parameter biases are also evaluated using tracks within jets