Pinned Repositories
3D-BoundingBox
PyTorch implementation for 3D Bounding Box Estimation Using Deep Learning and Geometry
chainer
A flexible framework of neural networks for deep learning
CSharp-Plugin
MEF plugin implementation example for C#
discord_music_bot
Faster-RCNN-TensorFlow-Python3
Tensorflow Faster R-CNN for Windows/Linux and Python 3 (3.5/3.6/3.7)
gas_analyser
instance-segmentation-pytorch
Semantic Instance Segmentation with a Discriminative Loss Function in PyTorch (https://arxiv.org/abs/1708.02551)
IPP-Tutorials
Intel Performance Primitives Function Usage Examples
neural_renderer
"Neural 3D Mesh Renderer" (CVPR 2018) by H. Kato, Y. Ushiku, and T. Harada.
neural_renderer_v2_pytorch
PyTorch implementation of original neural mesh renderer v2
dBeker's Repositories
dBeker/Faster-RCNN-TensorFlow-Python3
Tensorflow Faster R-CNN for Windows/Linux and Python 3 (3.5/3.6/3.7)
dBeker/CSharp-Plugin
MEF plugin implementation example for C#
dBeker/instance-segmentation-pytorch
Semantic Instance Segmentation with a Discriminative Loss Function in PyTorch (https://arxiv.org/abs/1708.02551)
dBeker/IPP-Tutorials
Intel Performance Primitives Function Usage Examples
dBeker/neural_renderer_v2_pytorch
PyTorch implementation of original neural mesh renderer v2
dBeker/3D-BoundingBox
PyTorch implementation for 3D Bounding Box Estimation Using Deep Learning and Geometry
dBeker/chainer
A flexible framework of neural networks for deep learning
dBeker/discord_music_bot
dBeker/gas_analyser
dBeker/kitti
Data loader for KITTI
dBeker/neural_renderer
"Neural 3D Mesh Renderer" (CVPR 2018) by H. Kato, Y. Ushiku, and T. Harada.
dBeker/markdown-cheatsheet
Markdown Cheatsheet for Github Readme.md
dBeker/monodepth
Unsupervised single image depth prediction with CNNs
dBeker/monodepth2
Monocular depth estimation from a single image
dBeker/pseudo_lidar
(CVPR 2019) Pseudo-LiDAR from Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Driving
dBeker/siren
Official implementation of "Implicit Neural Representations with Periodic Activation Functions"
dBeker/tutorials
Training material for IPU users: tutorials, feature examples, simple applications