Zobrazeno 1 - 10
of 52
pro vyhledávání: '"Vlad I. Morariu"'
Autor:
Puneet Mathur, Rajiv Jain, Ashutosh Mehra, Jiuxiang Gu, Franck Dernoncourt, Anandhavelu N, Quan Tran, Verena Kaynig-Fittkau, Ani Nenkova, Dinesh Manocha, Vlad I. Morariu
Publikováno v:
2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV).
Autor:
Debashish Pradhan, Tripti Rajput, Aravind Jembu Rajkumar, Jonathan Lazar, Rajiv Jain, Vlad I. Morariu, Varun Manjunatha
Publikováno v:
ACM Transactions on Accessible Computing. 15:1-52
Most PDF documents are inaccessible for people with disabilities, creating barriers in education, science, commerce, e-government, and recreation. Documents in PDF format are considered harder to make accessible than documents in other formats, prima
Autor:
Jason Kuen, Hongfu Liu, Vlad I. Morariu, Jiuxiang Gu, Varun Manjunatha, Rajiv Jain, Peizhao Li, Handong Zhao
Publikováno v:
CVPR
We propose SelfDoc, a task-agnostic pre-training framework for document image understanding. Because documents are multimodal and are intended for sequential reading, our framework exploits the positional, textual, and visual information of every sem
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6e68717d265d0e6ac01b30656c82c867
http://arxiv.org/abs/2106.03331
http://arxiv.org/abs/2106.03331
Autor:
Quan Hung Tran, Dinesh Manocha, Vlad I. Morariu, Rajiv Jain, Puneet Mathur, Franck Dernoncourt
Publikováno v:
ACL/IJCNLP (2)
We present TIMERS - a TIME, Rhetorical and Syntactic-aware model for document-level temporal relation classification in the English language. Our proposed method leverages rhetorical discourse features and temporal arguments from semantic role labels
Autor:
Joe Barrow, Varun Manjunatha, Franck Dernoncourt, Henning Wachsmuth, Philip Resnik, Rajiv Jain, Nedim Lipka, Douglas W. Oard, Vlad I. Morariu
Publikováno v:
ACL/IJCNLP (1)
Approaches to computational argumentation tasks such as stance detection and aspect detection have largely focused on the text of independent claims, losing out on potentially valuable context provided by the rest of the collection. We introduce a ge
Autor:
Vicente Ordonez, Vlad I. Morariu, Vitali Petsiuk, Kate Saenko, Rajiv Jain, Ashutosh Mehra, Varun Manjunatha
Publikováno v:
CVPR
We propose D-RISE, a method for generating visual explanations for the predictions of object detectors. Utilizing the proposed similarity metric that accounts for both localization and categorization aspects of object detection allows our method to p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6b558970d247c43187d73014b1cc515c
http://arxiv.org/abs/2006.03204
http://arxiv.org/abs/2006.03204
Autor:
Varun Manjunatha, Curtis Wigington, Chris Tensmeyer, Kai Li, Nikolaos Barmpalios, Vlad I. Morariu, Yun Fu, Handong Zhao, Tong Sun
Publikováno v:
CVPR
Decomposing images of document pages into high-level semantic regions (e.g., figures, tables, paragraphs), document object detection (DOD) is fundamental for downstream tasks like intelligent document editing and understanding. DOD remains a challeng
Autor:
Varun Manjunatha, Vicente Ordonez, Vlad I. Morariu, Pramuditha Perera, Vishal M. Patel, Curtis Wigington, Rajiv Jain
Publikováno v:
CVPR
We address the problem of open-set recognition, where the goal is to determine if a given sample belongs to one of the classes used for training a model (known classes). The main challenge in open-set recognition is to disentangle open-set samples th
Publikováno v:
ACL
Text segmentation aims to uncover latent structure by dividing text from a document into coherent sections. Where previous work on text segmentation considers the tasks of document segmentation and segment labeling separately, we show that the tasks