<?xml version="1.0" encoding="utf-8"?><!DOCTYPE article  PUBLIC '-//OASIS//DTD DocBook XML V4.4//EN'  'http://www.docbook.org/xml/4.4/docbookx.dtd'><article><articleinfo><title>AbstractIonascu</title><revhistory><revision><revnumber>2</revnumber><date>2023-04-01 12:56:20</date><authorinitials>DanielaZaharie</authorinitials></revision><revision><revnumber>1</revnumber><date>2023-04-01 12:55:47</date><authorinitials>DanielaZaharie</authorinitials></revision></revhistory></articleinfo><para><emphasis role="strong">3D Reconstructions Applied on Broadcast Sports</emphasis> </para><para>Alexandru Ionascu, West University of Timisoara </para><para><emphasis role="strong">Abstract:</emphasis> All the major broadcast partners provide 360 views in all the leading sports and further interactive scene synthesis for commentary and analysis. In addition, many triple-A video game studios use markerless optical tracking to create new animations.  In this talk, we will explore the possibilities by looking at broadcast-monocular football and tennis videos without additional sensors or data. To discuss the current state-of-the-art method, we typically refer to (1) complete 3D scenes with human body regression and neural rigging from video or (2) pseudo-3D environments with neural rendering pipelines (pix2pix or vid2vid). We will also introduce a sampling-based approach for video processing, and we can experiment with this technique for athlete 3D reconstruction on existing and new poses. </para></article>