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
Latest commit History 69 Commits
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