CS6476-TermProject

Project Website

DataExploration.ipynb - Exploring the dataset, and code to generate tailored dataset for limited predicates.
VisRel + All Pairs Detection.ipynb - Object Detection using Faster-RCNN and returning all possible BBox pairs.
BBoxMaskClassifier.ipynb - CNN classifier on top of bounding box masks.
TripletLossNN.ipynb - Model using Triplet Loss + BBox Mask + Glove embeddings.
BBoxWordEmbeddingModel.ipynb - Model using BBox Mask + Glove embeddings + AlexNet latent vector.
new_json_dataset - Tailored dataset for our 4 predicates, extracted from the VRD dataset.
triplets_dataset - <anchor, positive, negative> triplets mined for our triplet-based approach.
models - Contains our best models from the appraoches we tried.

Our best model can be found at : https://tinyurl.com/r9pldad

If you're having trouble viewing the notebook, copy the link to the .ipynb file into Jupyter Notebook Viewer!

Name		Name	Last commit message	Last commit date
models		models
new_json_dataset		new_json_dataset
triplets_dataset		triplets_dataset
utils		utils
.gitignore		.gitignore
BBoxMask+LatentVectors+WordEmbeddingsClassifier.ipynb		BBoxMask+LatentVectors+WordEmbeddingsClassifier.ipynb
BBoxMaskClassifier.ipynb		BBoxMaskClassifier.ipynb
DataExploration.ipynb		DataExploration.ipynb
Qualitative_Analysis.ipynb		Qualitative_Analysis.ipynb
README.md		README.md
TripletLossNN.ipynb		TripletLossNN.ipynb
VisRel + All Pairs Detection.ipynb		VisRel + All Pairs Detection.ipynb
requirements.txt		requirements.txt