DeepaliVerma's repositories
3DGNN_pytorch
3D Graph Neural Networks for RGBD Semantic Segmentation
adversarial
Creating and defending against adversarial examples
Automatic-Image-Captioning
Generating Captions for images using Deep Learning
awesome-scene-graphs
Literature survey of scene graphs
Awesome-Video-Captioning
video captioning
cosine_softmax_keras
Quick implementation of Deep Cosine Metric Learning for Person Re-Identification in Keras
Coursera-Machine-Learning
Coursera Machine Learning - Python code
FCN-for-Semantic-Segmentation
Implemention of FCN-8 and FCN-16 with Keras and uses CRF as post processing
fire-app-builder
Fire App Builder is a framework for building java media apps for Fire TV, allowing you to add your feed of media content to a configuration file and build an app to browse and play it quickly.
graph-networks
A list of interesting graph neural networks (GNN) links with a primary interest in recommendations and tensorflow that is continually updated and refined
keras-knowledge-distillation
Keras implementation of knowledge distillation(Hinton, et al. 2015)
OpenCV2-Python-Tutorials
This repo contains tutorials on OpenCV-Python library using new cv2 interface
ProcNets-YouCook2
Source code for paper "Towards Automatic Learning of Procedures from Web Instructional Videos"
Pytorch_C3D_Feature_Extractor
Pytorch C3D feature extractor
PyTorch_Image_Captioning
PyTorch Image Captioning CNN-RNN Model.
sc18-dl-tutorial
Keras tutorial code for the SC18 tutorial on Deep Learning at Scale
scene-graph-TF-release
"Scene Graph Generation by Iterative Message Passing" code repository
SCN_for_video_captioning
Using Semantic Compositional Networks for Video Captioning
social-graph
social network graph and recommendation systems based on collaborative filtering
spherical-cnn
Demo code for the paper "Learning SO(3) Equivariant Representations with Spherical CNNs"
Tensorflow-Computer-Vision-Tutorial
Tutorials of deep learning for computer vision.
Transfer-Learning-in-keras---custom-data
Implementing Transfer Learning for custom data using VGG-16 and Resnet-50
Video2Text
📺 An Encoder-Decoder Model for Sequence-to-Sequence learning: Video to Text