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💣🔥#Unity acquires Ziva Dynamics 💣🔥
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Real-time digital humans
✅A mix of #ML & biomechanics
✅Complex anatomical simulation
✅30 terabytes of 4D data
✅72,000 trained shapes
More: https://www.linkedin.com/posts/visionarynet_unity-metaverse-ml-activity-6891413170834030592-Rr9p
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Real-time digital humans
✅A mix of #ML & biomechanics
✅Complex anatomical simulation
✅30 terabytes of 4D data
✅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
💣🔥#Unity acquires Ziva Dynamics 💣🔥
👉Unity acquires Ziva Dynamics, leader in sophisticated simulation and deformation, machine learning, and real-time character creation. #Metaverse?
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Real-time SOTA in Unity for digital humans creation
✅A mix…
👉Unity acquires Ziva Dynamics, leader in sophisticated simulation and deformation, machine learning, and real-time character creation. #Metaverse?
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Real-time SOTA in Unity for digital humans creation
✅A mix…
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🧁🧁The definitive (recently updated) collection of neural pedestrian detectors🧁🧁
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Cascade Mask-R-CNN
✅Faster R-CNN
✅RetinaNet(Guided Anchoring)
✅Hybrid Task Cascade, MGAN, CSP
✅MMDetection/SwinTransformer
✅Code under Apache License 2.0
More: https://bit.ly/3KArsA1
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Cascade Mask-R-CNN
✅Faster R-CNN
✅RetinaNet(Guided Anchoring)
✅Hybrid Task Cascade, MGAN, CSP
✅MMDetection/SwinTransformer
✅Code under Apache License 2.0
More: https://bit.ly/3KArsA1
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🧃🧃Training ImageNet in minutes with FFCV🧃🧃
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Work with any existing code
✅Pre-fetching, caching, transfer
✅Fused-and-compiled data proc.
✅Multiple models per GPU
✅Tools for image handling
More: https://bit.ly/3IAZHW9
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Work with any existing code
✅Pre-fetching, caching, transfer
✅Fused-and-compiled data proc.
✅Multiple models per GPU
✅Tools for image handling
More: https://bit.ly/3IAZHW9
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🎨RePaint: new SOTA in inpainting🎨
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅RePaint via DDPM
✅Suitable with severe corruption
✅Pretrained DDPM as prior
✅SOTA vs Autoregressive/GAN
More: https://bit.ly/3AAk8jm
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅RePaint via DDPM
✅Suitable with severe corruption
✅Pretrained DDPM as prior
✅SOTA vs Autoregressive/GAN
More: https://bit.ly/3AAk8jm
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