http://digicrop.de/
The International Conference on Digital Technologies for Sustainable Crop Production will take place on November 1-10, 2020.
DIGICROP 2020 is a scientific event addressing an international and interdisciplinary audience working at the intersection of engineering, robotics, computer science, crop sciences, agricultural sciences, phenotyping, and economics. It brings together researchers across disciplines that develop, propose, use, or evaluate new digital technologies with the goal of making central contributions to sustainability in the context of crop production, crop breeding, biodiversity, or our ecosystems.
DIGICROP will offer a mix of keynote presentations, invited video talks, and submitted video talks. The aim of the conference is to stimulate scientific discussions among the participants. The conference will take place online.
📍Registration will be Free of charge.
The International Conference on Digital Technologies for Sustainable Crop Production will take place on November 1-10, 2020.
DIGICROP 2020 is a scientific event addressing an international and interdisciplinary audience working at the intersection of engineering, robotics, computer science, crop sciences, agricultural sciences, phenotyping, and economics. It brings together researchers across disciplines that develop, propose, use, or evaluate new digital technologies with the goal of making central contributions to sustainability in the context of crop production, crop breeding, biodiversity, or our ecosystems.
DIGICROP will offer a mix of keynote presentations, invited video talks, and submitted video talks. The aim of the conference is to stimulate scientific discussions among the participants. The conference will take place online.
📍Registration will be Free of charge.
Forwarded from Mohammad Sabokrou
All of the ASOC2020 presentations and Q&A sessions are currently available on the YouTube channel of "IPM AI GROUP": https://www.youtube.com/channel/UCLbQwn1n4XOhwXBC-fdoU3g
Forwarded from IPM- AI Group (Mohammad Sabokrou)
Several research positions in the following areas are available in our group(IPM, School of Computer Science, AI group).
Machine learning
computer vision
Natural language processing
Medical Imaging
Explanable AI
The appointments can be made at the levels of research assistant, senior research assistant, and postdoctoral. Interested applicants may send their CVs to sabokro@ipm.ir
Machine learning
computer vision
Natural language processing
Medical Imaging
Explanable AI
The appointments can be made at the levels of research assistant, senior research assistant, and postdoctoral. Interested applicants may send their CVs to sabokro@ipm.ir
Forwarded from IPM- AI Group (Mohammad Sabokrou)
IPM School of Computer Science is seeking a Postdoctoral researcher with a strong track record of publication in the area of Artificial Intelligence. If you are interested in joining us, please drop an email to sabokro@ipm.ir
Forwarded from Tensorflow(@CVision) (Alireza Akhavan)
#آخرین_مهلت ثبت نام
اولین جلسه ی دوره ی آنلاین GAN نهم اسفند است و ثبت نام تا پنج شنبه 7 اسفند خواهد بود.
http://class.vision/product/deep-generative-tf2/
اولین جلسه ی دوره ی آنلاین GAN نهم اسفند است و ثبت نام تا پنج شنبه 7 اسفند خواهد بود.
http://class.vision/product/deep-generative-tf2/
The submission website of the Second International Workshop on Holistic Video Understanding in Conjunction with #CVPR2021 is open. Accepted papers will be published via the Open Access versions, provided by the Computer Vision Foundation.
#LHVU
https://twitter.com/LSHVU/status/1366311041429352448?s=20
https://holistic-video-understanding.github.io/workshops/cvpr2021.html
#LHVU
https://twitter.com/LSHVU/status/1366311041429352448?s=20
https://holistic-video-understanding.github.io/workshops/cvpr2021.html
Twitter
Holistic Video Understanding
The submission website of the Second International Workshop on Holistic Video Understanding in Conjunction with #CVPR2021 is open. Accepted papers will be published via the Open Access versions, provided by the Computer Vision Foundation. https://t.co/gdtJpNgrhm
HVU2021 Call for paper
We present the Second International Workshop On Large Scale Holistic Video Understanding in conjunction with CVPR 2021. Holistic Video Understanding is a joint project of the KU Leuven, University of Bonn, KIT, ETH, and the HVU team.
We hope that HVU workshop establishes a video benchmark integrating joint recognition of all the semantic concepts, as a single class label per task is often not sufficient to describe the holistic content of a video. Further we invite the community to help to extend the HVU dataset that will spur research in video understanding as a comprehensive, multi-faceted problem.
We welcome contributions fitting the following research topics: Large scale video understanding; Multi-Modal learning from videos; Multi concept recognition from videos; Multi task deep neural networks for videos; Learning holistic representation from videos; Weakly supervised learning from web videos; Object, scene and event recognition from videos; Unsupervised video visual representation learning; Unsupervised and self-supervised learning with videos. Paper Submission
• Paper submission begins, Fabuary 20
• Paper submission deadline, March 31
• For more information visit: https://holistic-video-understanding.github.io/workshops/cvpr2021.html
• CMT submission website: https://cmt3.research.microsoft.com/HVU2021
Important dates
• Full Paper Deadline: March 31
• Notification of Acceptance: April 14
• Camera-ready Version: April 18
• Workshop date: TBA
Keynote Speakers
• Cordelia Schmid (Google AI)
• Joao Carreira (Google DeepMind)
• Carl Vondrick (Columbia University)
• Dima Damen (University of Bristol)
• Sanja Fidler (University of Toronto)
• Kristen Grauman (University of Texas at Austin)
Highlights
• TBD
If you have any questions, please contact us at https://twitter.com/LSHVU, over at https://github.com/holistic-video-understanding, or write to fayyaz@iai.uni-bonn.de.
Please feel free to forward this email to those who might be interested. We are looking forward to your HVU submissions!
Sincerely, The HVU 2021 Chairs
• Mohsen Fayyaz (University of Bonn)
• Vivek Sharm (MIT and Harvard)
• Ali Diba (KU Leuven)
• Luc Van Gool (ETH Zurich)
• Juergen Gall (University of Bonn)
• Ehsan Adeli (Stanford Vision and Learning)
• David Ross (Google AI)
• Rainer Stiefelhagen (Karlsruher Institut for Technology)
• Manohar Paluri (Facebook)
We present the Second International Workshop On Large Scale Holistic Video Understanding in conjunction with CVPR 2021. Holistic Video Understanding is a joint project of the KU Leuven, University of Bonn, KIT, ETH, and the HVU team.
We hope that HVU workshop establishes a video benchmark integrating joint recognition of all the semantic concepts, as a single class label per task is often not sufficient to describe the holistic content of a video. Further we invite the community to help to extend the HVU dataset that will spur research in video understanding as a comprehensive, multi-faceted problem.
We welcome contributions fitting the following research topics: Large scale video understanding; Multi-Modal learning from videos; Multi concept recognition from videos; Multi task deep neural networks for videos; Learning holistic representation from videos; Weakly supervised learning from web videos; Object, scene and event recognition from videos; Unsupervised video visual representation learning; Unsupervised and self-supervised learning with videos. Paper Submission
• Paper submission begins, Fabuary 20
• Paper submission deadline, March 31
• For more information visit: https://holistic-video-understanding.github.io/workshops/cvpr2021.html
• CMT submission website: https://cmt3.research.microsoft.com/HVU2021
Important dates
• Full Paper Deadline: March 31
• Notification of Acceptance: April 14
• Camera-ready Version: April 18
• Workshop date: TBA
Keynote Speakers
• Cordelia Schmid (Google AI)
• Joao Carreira (Google DeepMind)
• Carl Vondrick (Columbia University)
• Dima Damen (University of Bristol)
• Sanja Fidler (University of Toronto)
• Kristen Grauman (University of Texas at Austin)
Highlights
• TBD
If you have any questions, please contact us at https://twitter.com/LSHVU, over at https://github.com/holistic-video-understanding, or write to fayyaz@iai.uni-bonn.de.
Please feel free to forward this email to those who might be interested. We are looking forward to your HVU submissions!
Sincerely, The HVU 2021 Chairs
• Mohsen Fayyaz (University of Bonn)
• Vivek Sharm (MIT and Harvard)
• Ali Diba (KU Leuven)
• Luc Van Gool (ETH Zurich)
• Juergen Gall (University of Bonn)
• Ehsan Adeli (Stanford Vision and Learning)
• David Ross (Google AI)
• Rainer Stiefelhagen (Karlsruher Institut for Technology)
• Manohar Paluri (Facebook)
Microsoft
Conference Management Toolkit - Login
Microsoft's Conference Management Toolkit is a hosted academic conference management system. Modern interface, high scalability, extensive features and outstanding support are the signatures of Microsoft CMT.
Holistic Video Understanding Challenge @CVPR ‘21
https://competitions.codalab.org/competitions/29546
CHALLENGE IS OPEN!
Submission deadlines:
- With a CVF publication: date of workshop
- Without: week before date of workshop
Please submit submissions via: https://competitions.codalab.org/competitions/29546#participate-submit_results
In the last years, we have seen tremendous progress in the capabilities of computer systems to classify video clips taken from the Internet or to analyze human actions in videos. There are lots of works in video recognition field focusing on specific video understanding tasks, such as action recognition, scene understanding, etc. There have been great achievements in such tasks, however, there has not been enough attention toward the holistic video understanding task as a problem to be tackled.
Therefore, we issue this challenge, to tackle this problem on our dataset. For more information on the HVU dataset check the link below. The challenge focuses on the recognition of scenes, objects, actions, attributes, concepts and events in real-world user-generated videos. We expect you to annotate each video in our dataset with labels from a set of tags we provide, that have been sorted in the aforementioned categories. The results should be submitted in a CSV file on our submission sever, where it will be evaluated and ranked according to an assigned score, further information in the links below.
The top 10 scoring submissions will be asked to submit their code, further terms in the links below. The winning group must also submit an arXiv preprint report about their method.
Links:
- HVU workshop: https://holistic-video-understanding.github.io/workshops/cvpr2021.html
- On the dataset: https://holistic-video-understanding.github.io/
- Submission details: https://competitions.codalab.org/competitions/29546#learn_the_details-submission-format
- Evaluation details: https://competitions.codalab.org/competitions/29546#learn_the_details-evaluation
- Terms and Conditions: https://competitions.codalab.org/competitions/29546#learn_the_details-terms_and_conditions
For questions about the HVU challenge or the workshop, please contact fayyaz@iai.uni-bonn.de. Also, follow HVU on Twitter for the latest news: https://twitter.com/LSHVU or https://holistic-video-understanding.github.io/
Organizers:
- Mohsen Fayyaz, University of Bonn
- Ali Diba, KU Leuven
- Vivek Sharma, Harvard, MIT
- Luc Van Gool, ETH Zurich & KU Leuven
- Juergen Gall, University of Bonn
-Ehsan Adeli, Stanford
-David Ross, Google AI
- Rainer Stiefelhagen, KIT
- Manohar Paluri, Facebook AI
https://competitions.codalab.org/competitions/29546
CHALLENGE IS OPEN!
Submission deadlines:
- With a CVF publication: date of workshop
- Without: week before date of workshop
Please submit submissions via: https://competitions.codalab.org/competitions/29546#participate-submit_results
In the last years, we have seen tremendous progress in the capabilities of computer systems to classify video clips taken from the Internet or to analyze human actions in videos. There are lots of works in video recognition field focusing on specific video understanding tasks, such as action recognition, scene understanding, etc. There have been great achievements in such tasks, however, there has not been enough attention toward the holistic video understanding task as a problem to be tackled.
Therefore, we issue this challenge, to tackle this problem on our dataset. For more information on the HVU dataset check the link below. The challenge focuses on the recognition of scenes, objects, actions, attributes, concepts and events in real-world user-generated videos. We expect you to annotate each video in our dataset with labels from a set of tags we provide, that have been sorted in the aforementioned categories. The results should be submitted in a CSV file on our submission sever, where it will be evaluated and ranked according to an assigned score, further information in the links below.
The top 10 scoring submissions will be asked to submit their code, further terms in the links below. The winning group must also submit an arXiv preprint report about their method.
Links:
- HVU workshop: https://holistic-video-understanding.github.io/workshops/cvpr2021.html
- On the dataset: https://holistic-video-understanding.github.io/
- Submission details: https://competitions.codalab.org/competitions/29546#learn_the_details-submission-format
- Evaluation details: https://competitions.codalab.org/competitions/29546#learn_the_details-evaluation
- Terms and Conditions: https://competitions.codalab.org/competitions/29546#learn_the_details-terms_and_conditions
For questions about the HVU challenge or the workshop, please contact fayyaz@iai.uni-bonn.de. Also, follow HVU on Twitter for the latest news: https://twitter.com/LSHVU or https://holistic-video-understanding.github.io/
Organizers:
- Mohsen Fayyaz, University of Bonn
- Ali Diba, KU Leuven
- Vivek Sharma, Harvard, MIT
- Luc Van Gool, ETH Zurich & KU Leuven
- Juergen Gall, University of Bonn
-Ehsan Adeli, Stanford
-David Ross, Google AI
- Rainer Stiefelhagen, KIT
- Manohar Paluri, Facebook AI
Twitter
Holistic Video Understanding (@LSHVU) | Twitter
The latest Tweets from Holistic Video Understanding (@LSHVU). Holistic Video Understanding. Bonn, Karlsruhe, Leuven, California, Zurich
Forwarded from Mostafa
#PhD position at Inria (France):
"Robust and generalizable deep learning-based audio-visual speech enhancement"
Deadline to apply: 25/4/2021
Starting date: 1/10/2021
Duration: 3 years
More information:
https://jobs.inria.fr/public/classic/en/offres/2021-03399
"Robust and generalizable deep learning-based audio-visual speech enhancement"
Deadline to apply: 25/4/2021
Starting date: 1/10/2021
Duration: 3 years
More information:
https://jobs.inria.fr/public/classic/en/offres/2021-03399
Inria
PhD Position F/M Robust and Generalizable Deep Learning-based Audio-visual Speech Enhancement
Offre d'emploi Inria
The IPM AI group, is looking for a self-motivated research assistant to work on Explainable Artificial Intelligence. Send a message to "sabokro@ipm.ir" if you are interested.