Md Siyam Sajeeb Khan's repositories
aenet
AENet: audio feature extraction
aLSTMs
Codes for paper of "Attention-based LSTM with Semantic Consistency for Videos Captioning "
convert_torch_to_pytorch
Convert torch t7 model to pytorch model and source.
DeepCompletionRelease
Deep Depth Completion of a Single RGB-D Image
densevid_eval
Evaluation code for Dense-Captioning Events in Videos
lutorpy
Use torch in python for deep learning.
MonoDepth-PyTorch
Unofficial implementation of Unsupervised Monocular Depth Estimation neural network MonoDepth in PyTorch
Practical_RL-1
My solutions to Yandex Practical Reinforcement Learning course in PyTorch and Tensorflow
Predicting-Youtube-Video-Categories
Using data from the Youtube "Trending" page to predict the 'Category' of a video given the 'Title'.
pytorch-resnet3d
I3D Nonlocal ResNets in Pytorch
PyVideoResearch
A repository of common methods, datasets, and tasks for video research
RL-Adventure
Pytorch Implementation of DQN / DDQN / Prioritized replay/ noisy networks/ distributional values/ Rainbow/ hierarchical RL
sparse-to-dense
ICRA 2018 "Sparse-to-Dense: Depth Prediction from Sparse Depth Samples and a Single Image" (Torch Implementation)
sparse-to-dense.pytorch
ICRA 2018 "Sparse-to-Dense: Depth Prediction from Sparse Depth Samples and a Single Image" (PyTorch Implementation)
stafg-capgen-vid
automatic video caption generation with STA-FG framework
tum-ml
Exercises for the TUM machine learning course
Video-Classification-2-Stream-CNN
Video Classification using 2 stream CNN
video-classification-3d-cnn-pytorch
Video classification tools using 3D ResNet
video-content-description
Video content description technique for generating descriptions for unconstrained videos.
video_classification
This is a summary of deep learning based video classification methods.
Youtube-Video-Label-Classification
Youtube Video Label Classification using Single Frame model and Long-term Recurrent Convolutional Networks (LRCN) model
youtube_tag_predictor_sentiment_analysis
We are using YouTube videos to analyze and predict tags associated with each video using Machine Learning techniques and find interesting trends by performing sentiment analysis using Natural Language Processing on the top 10 trending videos in YouTube using title, description and comments.