Zobrazeno 1 - 10
of 31
pro vyhledávání: '"Anna Rohrbach"'
Recent studies have shown promising results in utilizing multimodal large language models (MLLMs) for computer vision tasks such as object detection and semantic segmentation. However, many challenging video tasks remain under-explored. Video-languag
Externí odkaz:
http://arxiv.org/abs/2406.18113
Autor:
Jinkyu Kim, Anna Rohrbach, Zeynep Akata, Suhong Moon, Teruhisa Misu, Yi‐Ting Chen, Trevor Darrell, John Canny
Publikováno v:
Applied AI Letters, Vol 2, Iss 4, Pp n/a-n/a (2021)
Abstract Humans learn to drive through both practice and theory, for example, by studying the rules, while most self‐driving systems are limited to the former. Being able to incorporate human knowledge of typical causal driving behavior should bene
Externí odkaz:
https://doaj.org/article/0b03332c2c2646a1a21cfb885107a291
Publikováno v:
Applied AI Letters, Vol 2, Iss 4, Pp n/a-n/a (2021)
Abstract We generate natural language explanations for a fine‐grained visual recognition task. Our explanations fulfill two criteria. First, explanations are class discriminative, meaning they mention attributes in an image which are important to i
Externí odkaz:
https://doaj.org/article/69ed6439dccc42589defb07bc3c6e376
Autor:
Jack Hessel, Jena D. Hwang, Jae Sung Park, Rowan Zellers, Chandra Bhagavatula, Anna Rohrbach, Kate Saenko, Yejin Choi
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031200588
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f039a20cbc68ecea512b1e7d14928f04
https://doi.org/10.1007/978-3-031-20059-5_32
https://doi.org/10.1007/978-3-031-20059-5_32
Publikováno v:
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies.
Autor:
Spencer Whitehead, Suzanne Petryk, Vedaad Shakib, Joseph Gonzalez, Trevor Darrell, Anna Rohrbach, Marcus Rohrbach
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031200588
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::57bb904fbd759b6707b9ae2f34566683
https://doi.org/10.1007/978-3-031-20059-5_9
https://doi.org/10.1007/978-3-031-20059-5_9
Publikováno v:
Applied AI Letters, Vol 2, Iss 4, Pp n/a-n/a (2021)
We generate natural language explanations for a fine‐grained visual recognition task. Our explanations fulfill two criteria. First, explanations are class discriminative, meaning they mention attributes in an image which are important to identify a
Autor:
John Canny, Teruhisa Misu, Chen Yi-Ting, Trevor Darrell, Zeynep Akata, Anna Rohrbach, Jinkyu Kim, Suhong Moon
Publikováno v:
Applied AI Letters, Vol 2, Iss 4, Pp n/a-n/a (2021)
Humans learn to drive through both practice and theory, for example, by studying the rules, while most self‐driving systems are limited to the former. Being able to incorporate human knowledge of typical causal driving behavior should benefit auton
Detecting out-of-context media, such as "mis-captioned" images on Twitter, is a relevant problem, especially in domains of high public significance. In this work we aim to develop defenses against such misinformation for the topics of Climate Change,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7d84700e5194833787fca86ba0c9eec8
Autor:
Roei Herzig, Elad Ben-Avraham, Karttikeya Mangalam, Amir Bar, Gal Chechik, Anna Rohrbach, Trevor Darrell, Amir Globerson
Recently, video transformers have shown great success in video understanding, exceeding CNN performance; yet existing video transformer models do not explicitly model objects, although objects can be essential for recognizing actions. In this work, w
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::457ada6210428d4e8a3a3f6f8b715301