126 research outputs found
Synthesizing Images of Humans in Unseen Poses
We address the computational problem of novel human pose synthesis. Given an
image of a person and a desired pose, we produce a depiction of that person in
that pose, retaining the appearance of both the person and background. We
present a modular generative neural network that synthesizes unseen poses using
training pairs of images and poses taken from human action videos. Our network
separates a scene into different body part and background layers, moves body
parts to new locations and refines their appearances, and composites the new
foreground with a hole-filled background. These subtasks, implemented with
separate modules, are trained jointly using only a single target image as a
supervised label. We use an adversarial discriminator to force our network to
synthesize realistic details conditioned on pose. We demonstrate image
synthesis results on three action classes: golf, yoga/workouts and tennis, and
show that our method produces accurate results within action classes as well as
across action classes. Given a sequence of desired poses, we also produce
coherent videos of actions.Comment: CVPR 201
Powers in a class of A-strict standard episturmian words
This paper concerns a specific class of strict standard episturmian words
whose directive words resemble those of characteristic Sturmian words. In
particular, we explicitly determine all integer powers occurring in such
infinite words, extending recent results of Damanik and Lenz (2003), who
studied powers in Sturmian words. The key tools in our analysis are canonical
decompositions and a generalization of singular words, which were originally
defined for the ubiquitous Fibonacci word. Our main results are demonstrated
via some examples, including the -bonacci word: a generalization of the
Fibonacci word to a -letter alphabet ().Comment: 26 pages; extended version of a paper presented at the 5th
International Conference on Words, Montreal, Canada, September 13-17, 200
Occurrences of palindromes in characteristic Sturmian words
This paper is concerned with palindromes occurring in characteristic Sturmian
words of slope , where is an irrational.
As is a uniformly recurrent infinite word, any (palindromic) factor
of occurs infinitely many times in with bounded gaps. Our
aim is to completely describe where palindromes occur in . In
particular, given any palindromic factor of , we shall establish
a decomposition of with respect to the occurrences of . Such a
decomposition shows precisely where occurs in , and this is
directly related to the continued fraction expansion of .Comment: 17 page
Painting Many Pasts: Synthesizing Time Lapse Videos of Paintings
We introduce a new video synthesis task: synthesizing time lapse videos
depicting how a given painting might have been created. Artists paint using
unique combinations of brushes, strokes, and colors. There are often many
possible ways to create a given painting. Our goal is to learn to capture this
rich range of possibilities.
Creating distributions of long-term videos is a challenge for learning-based
video synthesis methods. We present a probabilistic model that, given a single
image of a completed painting, recurrently synthesizes steps of the painting
process. We implement this model as a convolutional neural network, and
introduce a novel training scheme to enable learning from a limited dataset of
painting time lapses. We demonstrate that this model can be used to sample many
time steps, enabling long-term stochastic video synthesis. We evaluate our
method on digital and watercolor paintings collected from video websites, and
show that human raters find our synthetic videos to be similar to time lapse
videos produced by real artists. Our code is available at
https://xamyzhao.github.io/timecraft.Comment: 10 pages, CVPR 202
Visual Deprojection: Probabilistic Recovery of Collapsed Dimensions
We introduce visual deprojection: the task of recovering an image or video
that has been collapsed along a dimension. Projections arise in various
contexts, such as long-exposure photography, where a dynamic scene is collapsed
in time to produce a motion-blurred image, and corner cameras, where reflected
light from a scene is collapsed along a spatial dimension because of an edge
occluder to yield a 1D video. Deprojection is ill-posed-- often there are many
plausible solutions for a given input. We first propose a probabilistic model
capturing the ambiguity of the task. We then present a variational inference
strategy using convolutional neural networks as functional approximators.
Sampling from the inference network at test time yields plausible candidates
from the distribution of original signals that are consistent with a given
input projection. We evaluate the method on several datasets for both spatial
and temporal deprojection tasks. We first demonstrate the method can recover
human gait videos and face images from spatial projections, and then show that
it can recover videos of moving digits from dramatically motion-blurred images
obtained via temporal projection.Comment: ICCV 201
An absence of equipoise: Examining surgeons\u27 decision talk during encounters with women considering breast cancer surgery
Shared decision-making is recommended for decisions with multiple reasonable options, yet clinicians often subtly or explicitly guide choices. Using purposive sampling, we performed a secondary analysis of 142 audio-recorded encounters between 13 surgeons and women eligible for breast-conserving surgery with radiation or mastectomy. We trained 9 surgeons in shared decision-making and provided them one of two conversation aids; 4 surgeons practiced as usual. Based on a published taxonomy of treatment recommendations (pronouncements, suggestions, proposals, offers, assertions), we examined how surgeons framed choices with patients. Many surgeons made assertions providing information and advice (usual care 71% vs. intervention 66%; p = 0.54). Some made strong pronouncements (usual care 51% vs. intervention 36%; p = .09). Few made proposals and offers, leaving the door open for deliberation (proposals usual care 21% vs. intervention 26%; p = 0.51; offers usual care 40% vs. intervention 40%; p = 0.98). Surgeons were significantly more likely to describe options as comparable when using a conversation aid, mentioning this in all intervention group encounters (usual care 64% vs. intervention 100%; p\u3c0.001). Conversation aids can facilitate offers of comparable options, but other conversational actions can inhibit aspects of shared decision-making
Measuring organisational readiness for patient engagement (MORE) : an international online Delphi consensus study
Date of Acceptance: 28/01/2015. © 2015 Oostendorp et al.; licensee BioMed Central. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise statedWidespread implementation of patient engagement by organisations and clinical teams is not a reality yet. The aim of this study is to develop a measure of organisational readiness for patient engagement designed to monitor and facilitate a healthcare organisation’s willingness and ability to effectively implement patient engagement in healthcarePeer reviewedFinal Published versio
Identifying schizophrenia patients who carry pathogenic genetic copy number variants using standard clinical assessment: retrospective cohort study
Background
Copy number variants (CNVs) play a significant role in disease pathogenesis in a small subset of individuals with schizophrenia (~2.5%). Chromosomal microarray testing is a first-tier genetic test for many neurodevelopmental disorders. Similar testing could be useful in schizophrenia.
Aims
To determine whether clinically identifiable phenotypic features could be used to successfully model schizophrenia-associated (SCZ-associated) CNV carrier status in a large schizophrenia cohort.
Method
Logistic regression and receiver operating characteristic (ROC) curves tested the accuracy of readily identifiable phenotypic features in modelling SCZ-associated CNV status in a discovery data-set of 1215 individuals with psychosis. A replication analysis was undertaken in a second psychosis data-set (n = 479).
Results
In the discovery cohort, specific learning disorder (OR = 8.12; 95% CI 1.16–34.88, P = 0.012), developmental delay (OR = 5.19; 95% CI 1.58–14.76, P = 0.003) and comorbid neurodevelopmental disorder (OR = 5.87; 95% CI 1.28–19.69, P = 0.009) were significant independent variables in modelling positive carrier status for a SCZ-associated CNV, with an area under the ROC (AUROC) of 74.2% (95% CI 61.9–86.4%). A model constructed from the discovery cohort including developmental delay and comorbid neurodevelopmental disorder variables resulted in an AUROC of 83% (95% CI 52.0–100.0%) for the replication cohort.
Conclusions
These findings suggest that careful clinical history taking to document specific neurodevelopmental features may be informative in screening for individuals with schizophrenia who are at higher risk of carrying known SCZ-associated CNVs. Identification of genomic disorders in these individuals is likely to have clinical benefits similar to those demonstrated for other neurodevelopmental disorders
A three-talk model for shared decision making: multistage consultation process
© 2017 The Authors. Published by BMJ. This is an open access article available under a Creative Commons licence.
The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.1136/bmj.j4891Objectives To revise an existing three-talk model for learning how to achieve shared decision making, and to consult with relevant stakeholders to update and obtain wider engagement.
Design Multistage consultation process.
Setting Key informant group, communities of interest, and survey of clinical specialties.
Participants 19 key informants, 153 member responses from multiple communities of interest, and 316 responses to an online survey from medically qualified clinicians from six specialties.
Results After extended consultation over three iterations, we revised the three-talk model by making changes to one talk category, adding the need to elicit patient goals, providing a clear set of tasks for each talk category, and adding suggested scripts to illustrate each step. A new three-talk model of shared decision making is proposed, based on “team talk,” “option talk,” and “decision talk,” to depict a process of collaboration and deliberation. Team talk places emphasis on the need to provide support to patients when they are made aware of choices, and to elicit their goals as a means of guiding decision making processes. Option talk refers to the task of comparing alternatives, using risk communication principles. Decision talk refers to the task of arriving at decisions that reflect the informed preferences of patients, guided by the experience and expertise of health professionals.
Conclusions The revised three-talk model of shared decision making depicts conversational steps, initiated by providing support when introducing options, followed by strategies to compare and discuss trade-offs, before deliberation based on informed preferences
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