Gallery — Conference Paper

ACM DIS2020 Conference Long paper format. For more information see https://dis.acm.org/2020/

12th Edition of the Language Resources and Evaluation Conference LaTeX template. Source: https://lrec2020.lrec-conf.org/en/submission2020/authors-kit/.

Modelo para submissão no 4º Congresso Pós-Graduação do IFSP - 2019

Paper presented at ICCV 2019. This paper targets the task with discrete and periodic class labels (e.g., pose/orientation estimation) in the context of deep learning. The commonly used cross-entropy or regression loss is not well matched to this problem as they ignore the periodic nature of the labels and the class similarity, or assume labels are continuous value. We propose to incorporate inter-class correlations in a Wasserstein training framework by pre-defining (i.e., using arc length of a circle) or adaptively learning the ground metric. We extend the ground metric as a linear, convex or concave increasing function w.r.t. arc length from an optimization perspective. We also propose to construct the conservative target labels which model the inlier and outlier noises using a wrapped unimodal-uniform mixture distribution. Unlike the one-hot setting, the conservative label makes the computation of Wasserstein distance more challenging. We systematically conclude the practical closed-form solution of Wasserstein distance for pose data with either one-hot or conservative target label. We evaluate our method on head, body, vehicle and 3D object pose benchmarks with exhaustive ablation studies. The Wasserstein loss obtaining superior performance over the current methods, especially using convex mapping function for ground metric, conservative label, and closed-form solution.

This is a LaTeX template available for use in submitting manuscripts to the 12th ICCP hosted in 2020 in Minneapolis, Minnesota.

This is an UPDATED template suitable for submissions to the 14th Conference on Spatial Information Theory, which will be hosted by the Chair for Information Science at the University of Regensburg, Germany. It is a provided as a means of making things easier for those who might not be too familiar with writing LaTeX. The project uses NOW THE 2019 VERSION of the LIPICs class file. Submissions to the conference must adhere to the official LIPICs guidelines for authors to be found at: http://drops.dagstuhl.de/styles/lipics-v2019/lipics-v2019-authors.zip.

Sample document using the v2019 style version of the series OASIcs - OpenAccess Series in Informatics. OASIcs offers a venue for the Open Access and online publication of peer-reviewed proceedings based on international scientific events (workshops, symposia, conferences, ...) that took place outside of Schloss Dagstuhl. See https://www.dagstuhl.de/oasics https://github.com/dagstuhl-publishing/styles/

This is a sample file for legacy SIGCHI extended abstracts, using acmart.cls v1.71 (2020/05/04). Starting in Spring 2020 ACM retired SIGCHI Extended Abstract format (sigchi-a). ACM will not, under any circumstances, accept documents in this format for publication and will not offer technical support to the authors who use this template. You may use this format in the nonacm mode only, as in \documentclass[sigchi-a, nonacm]{acmart}.

This is a sample file for ACM SIGPLAN conference proceedings, using acmart.cls v2.08 (2024/06/04). It is provided by the ACM as a template for submissions, and pre-loaded in Overleaf (formerly writeLaTeX) for ease of editing online. Please see the ACM Submission Guidelines page for more details on manuscript preparation. Note: Most proceedings authors will use the "sigconf" proceedings template. If you are unsure which template variant to use, please request clarification from your event or publication contact. Important information regarding submission versions for review: After finalizing the formatting of your paper you must use the option “manuscript” with \documentclass[manuscript]{acmart} command. This will generate the output in single column review format which is required. Accepted manuscripts will be transformed during production to produce properly formatted output accord to the publication specifications. Authors will be provided the opportunity to review and approve the formatted output before the article is published to the ACM Digital Library.