└── README.md


/README.md:
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 1 | # MatConvNet contributions
 2 | 
 3 | This is a list of active MatConvNet contributed repositories.
 4 | 
 5 | They can be downloaded separately, or managed with the `vl_contrib` command (including compilation and setup; see `help vl_contrib`).
 6 | 
 7 | To add new repositories, open a Pull Request with your suggested changes (GitHub and BitBucket repositories are supported).
 8 | 
 9 | * [autonn](https://github.com/vlfeat/autonn) Automatic Differentiation engine for MatConvNet.
10 | * [curveball](https://github.com/jotaf98/curveball) Second-order optimiser for deep networks.
11 | * [schedule](https://github.com/jotaf98/schedule)  Scheduler for MatConvNet experiments, including grid and random searches, with multi-GPU support.
12 | * [convnet-burden](https://github.com/albanie/convnet-burden) Memory estimates/FLOP counting for convnet architectures.
13 | * [mcnSSD](https://github.com/albanie/mcnSSD) Single Shot Multi-box Detector (SSD).
14 | * [mcnFasterRCNN](https://github.com/albanie/mcnFasterRCNN) Faster R-CNN object detector.
15 | * [mcnRFCN](https://github.com/albanie/mcnRFCN) R-FCN object detector.
16 | * [mcnBReNorm](https://github.com/albanie/mcnBReNorm) Batch Renormalization.
17 | * [mcnPyTorch](https://github.com/albanie/mcnPyTorch) Tool for importing pytorch models into MatConvNet.
18 | * [mcnRobustLoss](https://github.com/albanie/mcnRobustLoss) Robust loss functions
19 | * [mcnMaxout](https://github.com/albanie/mcnMaxout) Maxout Networks.
20 | * [mcnResNeXt](https://github.com/albanie/mcnResNeXt) ResNeXt Models.
21 | * [mcnSENets](https://github.com/albanie/mcnSENets) Squeeze-and-Excitation Networks.
22 | * [mcnNMS](https://github.com/albanie/mcnNMS) GPU-based non-maximum supression.
23 | * [mcnColors](https://github.com/albanie/mcnColors) GPU-based color transformations.
24 | * [mcnMovingStats](https://github.com/albanie/mcnMovingStats) Online estimation of feature statistics.
25 | * [mcnExtraLayers](https://github.com/albanie/mcnExtraLayers) Additional layers for matconvnet.
26 | * [mcnDeepLab](https://github.com/albanie/mcnDeepLab) DeepLab segmentation.
27 | * [mcnGroupNorm](https://github.com/albanie/mcnGroupNorm) Group Normalization experiments.
28 | * [VGGVox](https://github.com/a-nagrani/VGGVox) VGGVox models trained on the VoxCeleb dataset.
29 | * [mcnDatasets](https://github.com/albanie/mcnDatasets) Common dataset imdb helpers.
30 | * [mcnFerPlus](https://github.com/albanie/mcnFerPlus) Emotion recognition on Fer2013+
31 | * [mcnToyOptim](https://github.com/albanie/mcnToyOptim) Toy datasets for optimiser comparison.
32 | * [mcnDCGAN](https://github.com/hbilen/mcnDCGAN) Deep Convolution Generative Adversarial Networks.
33 | * [mcnIm2row](https://github.com/albanie/mcnIm2row) MATLAB interface to the im2row function.
34 | * [siamese-mnist](https://github.com/lenck/siamese-mnist) MNIST Siamese Network example.
35 | * [dagnn_caffe_deploy](https://github.com/ecoto/dagnn_caffe_deploy) MatConvNet-DagNN to Caffe model converter.
36 | * [RotEqNet](https://github.com/di-marcos/RotEqNet) Rotation equivariant vector field networks.
37 | * [autonn-feedforward-texture-synthesis](https://github.com/ryanwebster90/autonn-feedforward-texture-synthesis) Feed forward texture synthesis in autonn.
38 | * [WSDDN](https://github.com/hbilen/WSDDN) Weakly Supervised Detection Networks
39 | * [mcnCrossModalEmotions](https://github.com/albanie/mcnCrossModalEmotions) Emotion Recognition in Speech using Cross-Modal Transfer in the Wild. 
40 | * [mcn-example-module](https://github.com/lenck/mcn-example-module) Example contribution repository, including C++/CUDA code compilation.
41 | 


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