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A community-maintained Python framework for creating mathematical animations.
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
You like pytorch? You like micrograd? You love tinygrad! ❤️
FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet.
Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.
A tour in the wonderland of math with python.
Best practice and tips & tricks to write scientific papers in LaTeX, with figures generated in Python or Matlab.
EAF, an extensible framework that revolutionizes the graphical capabilities of Emacs
Pytorch implementation of FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks
A transparent bridge between Git and Dropbox - use a Dropbox (shared) folder as a Git remote! 🎁
Unsupervised single image depth prediction with CNNs
Winning Solution in NTIRE19 Challenges on Video Restoration and Enhancement (CVPR19 Workshops) - Video Restoration with Enhanced Deformable Convolutional Networks. EDVR has been merged into BasicSR…
Deeper Depth Prediction with Fully Convolutional Residual Networks (FCRN)
A list of synthetic dataset and tools for computer vision
A proxy-less censorship resistance tool
Code of single-view depth prediction algorithm on Internet Photos described in "MegaDepth: Learning Single-View Depth Prediction from Internet Photos, Z. Li and N. Snavely, CVPR 2018".
Code for GeoNet: Unsupervised Learning of Dense Depth, Optical Flow and Camera Pose (CVPR 2018)
OptNet: Differentiable Optimization as a Layer in Neural Networks
Operator Discretization Library https://odlgroup.github.io/odl/
Augment Beancount importers with machine learning functionality.
[CVPR'20] Fast-MVSNet: Sparse-to-Dense Multi-View Stereo With Learned Propagation and Gauss-Newton Refinement
Learning Depth from Monocular Videos using Direct Methods, CVPR 2018