Architecture for real-time scene annotation (BlitzNet)
http://thoth.inrialpes.fr/research/blitznet/
ArxiV: https://arxiv.org/abs/1708.02813
GitHub: https://github.com/dvornikita/blitznet
#ICCV #github #dl #video
http://thoth.inrialpes.fr/research/blitznet/
ArxiV: https://arxiv.org/abs/1708.02813
GitHub: https://github.com/dvornikita/blitznet
#ICCV #github #dl #video
GitHub
GitHub - dvornikita/blitznet: Deep neural network for object detection and semantic segmentation in real-time. Official code forβ¦
Deep neural network for object detection and semantic segmentation in real-time. Official code for the paper "BlitzNet: A Real-Time Deep Network for Scene Understanding" - dvornik...
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FUNIT: Few-Shot Unsupervised Image-to-Image Translation
A team of NVIDIA researchers has defined new AI techniques that give computers enough smarts to see a picture of one animal and recreate its expression and pose on the face of any other creature. The work is powered in part by generative adversarial networks (GANs), an emerging AI technique that pits one neural network against another.
Blog: https://blogs.nvidia.com/blog/2019/10/27/ai-gans-pets-ganimals/
Paper: https://arxiv.org/abs/1905.01723
Π‘ode: https://github.com/NVlabs/FUNIT
GANimal app: http://nvidia-research-mingyuliu.com/ganimal/
#CV #GAN #ICCV
A team of NVIDIA researchers has defined new AI techniques that give computers enough smarts to see a picture of one animal and recreate its expression and pose on the face of any other creature. The work is powered in part by generative adversarial networks (GANs), an emerging AI technique that pits one neural network against another.
Blog: https://blogs.nvidia.com/blog/2019/10/27/ai-gans-pets-ganimals/
Paper: https://arxiv.org/abs/1905.01723
Π‘ode: https://github.com/NVlabs/FUNIT
GANimal app: http://nvidia-research-mingyuliu.com/ganimal/
#CV #GAN #ICCV
ββSinGan: Learning a Generative Model from a Single Natural Image
Best Paper Award at #ICCV2019. A generative model, which learns from a single natural image, and then generates random samples.
ArXiV: https://arxiv.org/pdf/1905.01164v2.pdf
Github: https://github.com/tamarott/SinGAN
#GAN #ICCV #BestPaperAward
Best Paper Award at #ICCV2019. A generative model, which learns from a single natural image, and then generates random samples.
ArXiV: https://arxiv.org/pdf/1905.01164v2.pdf
Github: https://github.com/tamarott/SinGAN
#GAN #ICCV #BestPaperAward
