Weakly-supervised Pre-training for 3D Human Pose Estimation via Perspective Knowledge

Modern deep learning-based 3D pose estimation approaches require plenty of 3D pose annotations. However, existing 3D datasets lack diversity, which limits the performance of current methods and their generalization ability. Although existing methods utilize 2D pose annotations to help 3D pose estimation, they mainly focus on extracting 2D structural constraints from 2D poses, ignoring the 3D information hidden in the images. In this paper, we propose a novel method to extract weak 3D information directly from 2D images without 3D pose supervision. Firstly, we utilize 2D pose annotations and perspective prior knowledge to generate the relationship of that keypoint is closer or farther from the camera, called relative depth. We collect a 2D pose dataset (MCPC) and generate relative depth labels. Based on MCPC, we propose a weakly-supervised pre-training (WSP) strategy to distinguish the depth relationship between two points in an image. WSP enables the learning of the relative depth of two keypoints on lots of in-the-wild images, which is more capable of predicting depth and generalization ability for 3D human pose estimation. After fine-tuning on 3D pose datasets, WSP achieves state-of-the-art results on two widely-used benchmarks

Fused Text Segmentation Networks for Multi-oriented Scene Text Detection

In this paper, we introduce a novel end-end framework for multi-oriented scene text detection from an instance-aware semantic segmentation perspective. We present Fused Text Segmentation Networks, which combine multi-level features during the feature extracting as text instance may rely on finer feature expression compared to general objects. It detects and segments the text instance jointly and simultaneously, leveraging merits from both semantic segmentation task and region proposal based object detection task. Not involving any extra pipelines, our approach surpasses the current state of the art on multi-oriented scene text detection benchmarks: ICDAR2015 Incidental Scene Text and MSRA-TD500 reaching Hmean 84.1% and 82.0% respectively. Morever, we report a baseline on total-text containing curved text which suggests effectiveness of the proposed approach.Comment: Accepted by ICPR201

Delayed Product Introduction

We investigate the incentives of a monopolistic seller to delay the introduction of a new and improved version of his product. By analyzing a three-period model, we show that the seller may prefer to delay introducing a new product, even though the enabling technologies for the product are already available. The underlying motivation is analogous to that found in the durable goods monopolist literature – the seller suffers from a time inconsistency problem that causes his old and new products to cannibalize each other. Without the ability to remove existing stock of the old product from the market, shorten product durability, or pace research and development (R&D), he may respond by selling the new product later. We characterize the equilibria with delayed introduction, and study their changes with respect to market and product parameters. In particular, we show that delayed introduction could occur regardless of whether the seller can offer upgrade discounts to consumers, that instead, it is related to quality improvement brought about by the new product, durabilities, and discount factors. Further, we show that delayed introduction could bring socially efficient outcomes as well. Based on the insights of the model, we provide practical suggestions on pricing and policies

A Qualitative Pilot Study on Text Messaging Intervention for Weight Loss in Adults

Background Overweight and obesity are major risk factors for chronic illnesses such as cancer, diabetes and cardiovascular diseases. Newfoundland and Labrador (NL) has the highest rates of overweight and obesity of all provinces in Canada. Mobile health or mhealth in the form of text messaging is a potential solution to addressing the high overweight and obesity rates of the province. In this study, we explored NL residents’ perceptions of text message programs as an effective intervention for weight loss. Methods This study utilized a descriptive qualitative design through in-person semi-structured interviews with adults with previous or current experience in a weight loss program. Participants were recruited through recurrent postings on a biweekly school newsletter and study posters throughout the medical school at Memorial University. The data were analyzed using deductive thematic analysis. Results This pilot study included two participants, both women. The themes that arose in this study included past positive experiences, past negative experiences, barriers for weight loss, motivation for weight loss, attitudes about text messaging-based weight loss interventions and specific suggestions for future app development. The latter included text message content with reminders and encouragement, group messages, interactive and personal text messages and specific goal-setting in the app. Interpretation There were mixed attitudes towards using a text messaging based intervention. Findings revealed motivating factors of accountability, seeing positive physical bodily changes and goal-setting. Both participants had similar suggestions regarding future app development that involved creating a personalized and interactive experience for the users and to include a sense of community and communication across users of the app

A Hybrid Model for Sense Guessing of Chinese Unknown Words

PACLIC 23 / City University of Hong Kong / 3-5 December 200