#مقاله #سورس_کد
حذف اشیاء از ویدیو با کیفیت عالی
Deep Flow-Guided Video Inpainting (#CVPR2019)
🎥Video Demo:
https://www.dropbox.com/s/2avcy30mleqi5vk/supplementary_cvpr_2019.mp4?dl=0
🔗project page:
https://nbei.github.io/video-inpainting.html
🔗paper:
https://arxiv.org/abs/1905.02884
🔗source code:
https://github.com/nbei/Deep-Flow-Guided-Video-Inpainting
(به زودی منتشر خواهد شد)
#Inpainting
حذف اشیاء از ویدیو با کیفیت عالی
Deep Flow-Guided Video Inpainting (#CVPR2019)
🎥Video Demo:
https://www.dropbox.com/s/2avcy30mleqi5vk/supplementary_cvpr_2019.mp4?dl=0
🔗project page:
https://nbei.github.io/video-inpainting.html
🔗paper:
https://arxiv.org/abs/1905.02884
🔗source code:
https://github.com/nbei/Deep-Flow-Guided-Video-Inpainting
(به زودی منتشر خواهد شد)
#Inpainting
#مقاله #سورس_کد #مجموعه_داده
CVPR’19 paper on speech-to-gesture prediction. Given raw speech audio, predict arm/hand motion to go along with it. Check out video, or download 128 hours of video for 10 speakers
Learning Individual Styles of Conversational Gesture
http://people.eecs.berkeley.edu/~shiry/speech2gesture/
#CVPR2019
🙏Thanks to: @ArtificialIntelligenceArticles
CVPR’19 paper on speech-to-gesture prediction. Given raw speech audio, predict arm/hand motion to go along with it. Check out video, or download 128 hours of video for 10 speakers
Learning Individual Styles of Conversational Gesture
http://people.eecs.berkeley.edu/~shiry/speech2gesture/
#CVPR2019
🙏Thanks to: @ArtificialIntelligenceArticles
#مقاله #سورس_کد
#CVPR2019 #face
Learning to Regress 3D Face Shape and Expressionfrom an Image without 3D Supervision
Get 3D faces from an image using RingNet. New CVPR paper with code on-line. The output is a 3D face/head model that can be animated. We do this with paired 3D-image training data.
#Video:
https://youtu.be/6wPQaJBgreE
#Source Code (#Tensorflow):
https://github.com/soubhiksanyal/RingNet
#Project_page:
https://ringnet.is.tue.mpg.de/
paper:
https://ps.is.tuebingen.mpg.de/uploads_file/attachment/attachment/509/paper_camera_ready.pdf
#CVPR2019 #face
Learning to Regress 3D Face Shape and Expressionfrom an Image without 3D Supervision
Get 3D faces from an image using RingNet. New CVPR paper with code on-line. The output is a 3D face/head model that can be animated. We do this with paired 3D-image training data.
#Video:
https://youtu.be/6wPQaJBgreE
#Source Code (#Tensorflow):
https://github.com/soubhiksanyal/RingNet
#Project_page:
https://ringnet.is.tue.mpg.de/
paper:
https://ps.is.tuebingen.mpg.de/uploads_file/attachment/attachment/509/paper_camera_ready.pdf
YouTube
RingNet: Learning to Regress 3D Face Shape and Expression from an Image without 3D Supervision
The estimation of 3D face shape from a single image must be robust to variations in lighting, head pose, expression, facial hair, makeup, and occlusions. Robustness requires a large training set of in-the-wild images, which by construction, lack ground truth…