Difference between revisions of "Conditional Adversarial Architecture (CAA)"
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* [http://blog.acolyer.org/2018/05/08/image-to-image-translation-with-conditional-adversarial-networks/ Image-to-image translation with conditional adversarial networks | Isola et al.] | * [http://blog.acolyer.org/2018/05/08/image-to-image-translation-with-conditional-adversarial-networks/ Image-to-image translation with conditional adversarial networks | Isola et al.] | ||
| − | * [http://sleep.csail.mit.edu/ Learning Sleep Stages from Radio Signals: A Conditional Adversarial Architecture | Mingmin Zhao, Shichao Yue, Dina Katabi, Tommi Jaakkola, Matt Bianchi - | + | * [http://sleep.csail.mit.edu/ Learning Sleep Stages from Radio Signals: A Conditional Adversarial Architecture | Mingmin Zhao, Shichao Yue, Dina Katabi, Tommi Jaakkola, Matt Bianchi - Massachusetts Institute of Technology (MIT) & Massachusetts General Hospital] |
| − | Massachusetts Institute of Technology (MIT) & Massachusetts General Hospital] | + | * [http://www.ncbi.nlm.nih.gov/pubmed/30180591 Entangled Conditional Adversarial Autoencoder for de Novo Drug Discovery | Polykovskiy D, Zhebrak A, Vetrov D, Ivanenkov Y, Aladinskiy V, Mamoshina P, Bozdaganyan M, Aliper A, Zhavoronkov A, Kadurin A] |
Occlusion is a fundamental problem in human pose estimation and many other vision tasks. Instead of hallucinating missing body parts based on visible ones, we demonstrate a solution that leverages radio signals to accurately track the 2D human pose through walls and obstructions. [http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhao_Through-Wall_Human_Pose_CVPR_2018_paper.pdf Through-Wall Human Pose Estimation Using Radio Signals | Mingmin Zhao, Tianhong Li, Mohammad Abu, Alsheikh Yonglong, Tian Hang Zhao, Antonio Torralba, Dina Katabi - MIT CSAIL] | Occlusion is a fundamental problem in human pose estimation and many other vision tasks. Instead of hallucinating missing body parts based on visible ones, we demonstrate a solution that leverages radio signals to accurately track the 2D human pose through walls and obstructions. [http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhao_Through-Wall_Human_Pose_CVPR_2018_paper.pdf Through-Wall Human Pose Estimation Using Radio Signals | Mingmin Zhao, Tianhong Li, Mohammad Abu, Alsheikh Yonglong, Tian Hang Zhao, Antonio Torralba, Dina Katabi - MIT CSAIL] | ||
https://www.researchgate.net/profile/Mingmin_Zhao3/publication/328049475/figure/fig2/AS:677681750351875@1538583328633/Our-teacher-student-network-model-used-in-RF-Pose-The-upper-pipeline-provides-training.png | https://www.researchgate.net/profile/Mingmin_Zhao3/publication/328049475/figure/fig2/AS:677681750351875@1538583328633/Our-teacher-student-network-model-used-in-RF-Pose-The-upper-pipeline-provides-training.png | ||
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<youtube>kBFMsY5ZP0o</youtube> | <youtube>kBFMsY5ZP0o</youtube> | ||
| + | <youtube>425rPG580dQ</youtube> | ||
| + | <youtube>l_NA911jMZs</youtube> | ||
<youtube>HgDdaMy8KNE</youtube> | <youtube>HgDdaMy8KNE</youtube> | ||
Revision as of 22:34, 17 October 2018
- Image-to-image translation with conditional adversarial networks | Isola et al.
- Learning Sleep Stages from Radio Signals: A Conditional Adversarial Architecture | Mingmin Zhao, Shichao Yue, Dina Katabi, Tommi Jaakkola, Matt Bianchi - Massachusetts Institute of Technology (MIT) & Massachusetts General Hospital
- Entangled Conditional Adversarial Autoencoder for de Novo Drug Discovery | Polykovskiy D, Zhebrak A, Vetrov D, Ivanenkov Y, Aladinskiy V, Mamoshina P, Bozdaganyan M, Aliper A, Zhavoronkov A, Kadurin A
Occlusion is a fundamental problem in human pose estimation and many other vision tasks. Instead of hallucinating missing body parts based on visible ones, we demonstrate a solution that leverages radio signals to accurately track the 2D human pose through walls and obstructions. Through-Wall Human Pose Estimation Using Radio Signals | Mingmin Zhao, Tianhong Li, Mohammad Abu, Alsheikh Yonglong, Tian Hang Zhao, Antonio Torralba, Dina Katabi - MIT CSAIL
