Zobrazeno 1 - 10
of 71
pro vyhledávání: '"Ross Girshick"'
Autor:
Omri Bar, Daniel Neimark, Maya Zohar, Gregory D. Hager, Ross Girshick, Gerald M. Fried, Tamir Wolf, Dotan Asselmann
Publikováno v:
Scientific Reports, Vol 10, Iss 1, Pp 1-12 (2020)
Abstract AI is becoming ubiquitous, revolutionizing many aspects of our lives. In surgery, it is still a promise. AI has the potential to improve surgeon performance and impact patient care, from post-operative debrief to real-time decision support.
Externí odkaz:
https://doaj.org/article/7ac9ed46cc5e42b98872a44472665647
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031200762
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6dd6a125cd02413c59a55c42605d9072
https://doi.org/10.1007/978-3-031-20077-9_17
https://doi.org/10.1007/978-3-031-20077-9_17
Autor:
Jitendra Malik, Haoqi Fan, Ross Girshick, Aaron Adcock, Matt Feiszli, Haichuan Yang, Bo Xiong, Nikhila Ravi, Yanghao Li, Christoph Feichtenhofer, Tullie Murrell, Heng Wang, Kalyan Vasudev Alwala, Meng Li, Wan-Yen Lo, Yilei Li
Publikováno v:
ACM Multimedia
We introduce PyTorchVideo, an open-source deep-learning library that provides a rich set of modular, efficient, and reproducible components for a variety of video understanding tasks, including classification, detection, self-supervised learning, and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::41950dc1e1f1cc0f6f48cfaea938e168
http://arxiv.org/abs/2111.09887
http://arxiv.org/abs/2111.09887
Publikováno v:
CVPR
We present Boundary IoU (Intersection-over-Union), a new segmentation evaluation measure focused on boundary quality. We perform an extensive analysis across different error types and object sizes and show that Boundary IoU is significantly more sens
Publikováno v:
CVPR
We present a large-scale study on unsupervised spatiotemporal representation learning from videos. With a unified perspective on four recent image-based frameworks, we study a simple objective that can easily generalize all these methods to space-tim
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9acab0695cca3cc1f15a2f178a7c30c6
http://arxiv.org/abs/2104.14558
http://arxiv.org/abs/2104.14558
Publikováno v:
CVPR
In this work we analyze strategies for convolutional neural network scaling; that is, the process of scaling a base convolutional network to endow it with greater computational complexity and consequently representational power. Example scaling strat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ae9c7bbc92e19808a708767b39fc80c4
http://arxiv.org/abs/2103.06877
http://arxiv.org/abs/2103.06877
Autor:
Ross Girshick, Maya Zohar, Dotan Asselmann, Gerald M. Fried, Omri Bar, Tamir Wolf, Gregory D. Hager, Daniel Neimark
Publikováno v:
Scientific Reports, Vol 10, Iss 1, Pp 1-12 (2020)
Scientific Reports
Scientific Reports
AI is becoming ubiquitous, revolutionizing many aspects of our lives. In surgery, it is still a promise. AI has the potential to improve surgeon performance and impact patient care, from post-operative debrief to real-time decision support. But, how
Autor:
Alex Xiao, Geoffrey Zweig, Christian Fuegen, Ross Girshick, Yatharth Saraf, Abdelrahman Mohamed, Kritika Singh, Sergey Edunov, Vitaliy Liptchinsky, Vimal Manohar
Publikováno v:
INTERSPEECH
Many semi- and weakly-supervised approaches have been investigated for overcoming the labeling cost of building high quality speech recognition systems. On the challenging task of transcribing social media videos in low-resource conditions, we conduc
Publikováno v:
CVPR
We present a new method for efficient high-quality image segmentation of objects and scenes. By analogizing classical computer graphics methods for efficient rendering with over- and undersampling challenges faced in pixel labeling tasks, we develop
Publikováno v:
CVPR
We present Momentum Contrast (MoCo) for unsupervised visual representation learning. From a perspective on contrastive learning as dictionary look-up, we build a dynamic dictionary with a queue and a moving-averaged encoder. This enables building a l