Gallery — Conference Paper

An unofficial LaTeX template for Transportation Research Board (TRB) submission. Repository: https://github.com/wklchris/TRB-template

This is the template for the Cryptography and Information Security Conference (CISC). Due to copyright concerns about the BiauKai font, this template uses AR PL UKai TW as the main CJK font instead. But you're still able to upload the font to Overleaf by yourself. Notice: \nocite{*} is used to display reference examples. You should delete this line. The default template is for Chinese paper, please change the following parameters to the English version. labelsep = period % English = period, Chinese = space \renewcommand{\Authsep}{~} \renewcommand{\Authand}{~} \renewcommand{\Authands}{~} \renewcommand\figurename{圖} \renewcommand\tablename{表} \renewcommand\refname{參考文獻} % comment out these lines for English paper \parindent=1em % English = 1em, Chinese = 2em

This is a sample file for ACM SIG conference proceedings with the acmsmall format specifications, 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: There are only a small group of ACM conferences which permitted to use this 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.

The paper template for CiiS2021

Submission Template for AH2020

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.