Channel name was changed to Β«Deep LearningΒ»
Channel name was changed to Β«AI & Deep LearningΒ»
π£π₯#Unity acquires Ziva Dynamics π£π₯
ππ’π π‘π₯π’π π‘ππ¬:
β Real-time digital humans
β A mix of #ML & biomechanics
β Complex anatomical simulation
β 30 terabytes of 4D data
β 72,000 trained shapes
More: https://www.linkedin.com/posts/visionarynet_unity-metaverse-ml-activity-6891413170834030592-Rr9p
ππ’π π‘π₯π’π π‘ππ¬:
β Real-time digital humans
β A mix of #ML & biomechanics
β Complex anatomical simulation
β 30 terabytes of 4D data
β 72,000 trained shapes
More: https://www.linkedin.com/posts/visionarynet_unity-metaverse-ml-activity-6891413170834030592-Rr9p
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#unity #metaverse #ml #deeplearning #ai #ai #artificialintelligence⦠| Alessandro Ferrari | 22 comments
π£π₯#Unity acquires Ziva Dynamics π£π₯
πUnity acquires Ziva Dynamics, leader in sophisticated simulation and deformation, machine learning, and real-time character creation. #Metaverse?
ππ’π π‘π₯π’π π‘ππ¬:
β Real-time SOTA in Unity for digital humans creation
β A mixβ¦
πUnity acquires Ziva Dynamics, leader in sophisticated simulation and deformation, machine learning, and real-time character creation. #Metaverse?
ππ’π π‘π₯π’π π‘ππ¬:
β Real-time SOTA in Unity for digital humans creation
β A mixβ¦
π€1π±1
π§π§The definitive (recently updated) collection of neural pedestrian detectorsπ§π§
ππ’π π‘π₯π’π π‘ππ¬:
β Cascade Mask-R-CNN
β Faster R-CNN
β RetinaNet(Guided Anchoring)
β Hybrid Task Cascade, MGAN, CSP
β MMDetection/SwinTransformer
β Code under Apache License 2.0
More: https://bit.ly/3KArsA1
ππ’π π‘π₯π’π π‘ππ¬:
β Cascade Mask-R-CNN
β Faster R-CNN
β RetinaNet(Guided Anchoring)
β Hybrid Task Cascade, MGAN, CSP
β MMDetection/SwinTransformer
β Code under Apache License 2.0
More: https://bit.ly/3KArsA1
π₯2π€©2π1π±1
π§π§Training ImageNet in minutes with FFCVπ§π§
ππ’π π‘π₯π’π π‘ππ¬:
β Work with any existing code
β Pre-fetching, caching, transfer
β Fused-and-compiled data proc.
β Multiple models per GPU
β Tools for image handling
More: https://bit.ly/3IAZHW9
ππ’π π‘π₯π’π π‘ππ¬:
β Work with any existing code
β Pre-fetching, caching, transfer
β Fused-and-compiled data proc.
β Multiple models per GPU
β Tools for image handling
More: https://bit.ly/3IAZHW9
π3π₯1π€©1
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π¨RePaint: new SOTA in inpaintingπ¨
ππ’π π‘π₯π’π π‘ππ¬:
β RePaint via DDPM
β Suitable with severe corruption
β Pretrained DDPM as prior
β SOTA vs Autoregressive/GAN
More: https://bit.ly/3AAk8jm
ππ’π π‘π₯π’π π‘ππ¬:
β RePaint via DDPM
β Suitable with severe corruption
β Pretrained DDPM as prior
β SOTA vs Autoregressive/GAN
More: https://bit.ly/3AAk8jm
π€©4π€―1
Channel name was changed to Β«AI & Deep Learning (with papers)Β»
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π π Re-inventing the animationπ π
ππ’π π‘π₯π’π π‘ππ¬:
β S2PR: engineers + artists
β Style2Paint: a coloring software
β Style2Paints -> βSePaβ
β Source code under Apache
More: https://bit.ly/3rPZPu4
ππ’π π‘π₯π’π π‘ππ¬:
β S2PR: engineers + artists
β Style2Paint: a coloring software
β Style2Paints -> βSePaβ
β Source code under Apache
More: https://bit.ly/3rPZPu4
π2
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π½ ManyDepth: adaptive 3D-depth π½
ππ’π π‘π₯π’π π‘ππ¬:
β SSL-training, monocular only
β No depths or poses needed
β Adaptive cost volume
β Handling moving objects
β Patent Pendingπ
More: https://bit.ly/3fZpIlD
ππ’π π‘π₯π’π π‘ππ¬:
β SSL-training, monocular only
β No depths or poses needed
β Adaptive cost volume
β Handling moving objects
β Patent Pendingπ
More: https://bit.ly/3fZpIlD
π4β€2π₯1π±1
π₯The power of Transformersπ₯
π100+ official implementations, papers, github repo and colab of:
01 GPT-Neo 2021
02 Transformer 2017
03 BERT 2018
04 GPT 2018
05 Univ.Transformer 2018
06 T-D 2018
07 GPT-2 2019
08 T5 2019
09 BART 2019
10 XLNet 2019
11...
πThe full list: https://github.com/ashishpatel26/Treasure-of-Transformers
π100+ official implementations, papers, github repo and colab of:
01 GPT-Neo 2021
02 Transformer 2017
03 BERT 2018
04 GPT 2018
05 Univ.Transformer 2018
06 T-D 2018
07 GPT-2 2019
08 T5 2019
09 BART 2019
10 XLNet 2019
11...
πThe full list: https://github.com/ashishpatel26/Treasure-of-Transformers
π₯5β€1π€©1
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βοΈTransformers in Medical βοΈ
π100+ papers, implementations and code of Transformers in medical imaging.
ππ’π π‘π₯π’π π‘ππ¬:
β Medical Image Segmentation
β Medical Image Classification
β Medical Image Reconstruction
β Medical Image Registration
β Medical Image Synthesis
β Medical Image Detection
β Clinical Report Generation
β Survey and more..
The full list: https://bit.ly/3ILzswl
π100+ papers, implementations and code of Transformers in medical imaging.
ππ’π π‘π₯π’π π‘ππ¬:
β Medical Image Segmentation
β Medical Image Classification
β Medical Image Reconstruction
β Medical Image Registration
β Medical Image Synthesis
β Medical Image Detection
β Clinical Report Generation
β Survey and more..
The full list: https://bit.ly/3ILzswl
π4π₯2π€―1
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πͺ#3D with Transformersπͺ
πShapeFormer, transformer network for incomplete input
β VQDIF representation for 3D
β Transformer-based model
β Partial input -> completed shape
β ConvONet/Taming-transf/DCTransf.
β SOTA for #3D shape completion
More: https://bit.ly/3s0D2f1
πShapeFormer, transformer network for incomplete input
β VQDIF representation for 3D
β Transformer-based model
β Partial input -> completed shape
β ConvONet/Taming-transf/DCTransf.
β SOTA for #3D shape completion
More: https://bit.ly/3s0D2f1
β€4π1π₯1π1