Final Project - inspirations, datasets and papers

Interesting papers

To inspire project ideas, here are some cool NLP papers:

• Attention is All You Need
• Quasi-Recurrent Neural Networks
• Semi-supervised Sequence Learning
• A Joint Many-Task Model: Growing a Neural Network for Multiple NLP Tasks
• Semi-supervised sequence tagging with bidirectional language models
• Deep Biaffine Attention for Neural Dependency Parsing
• Generating Sentences from a Continuous Space
• Improving Neural Language Models with a Continuous Cache
• Reasoning about Entailment with Neural Attention
• Ultradense Word Embeddings by Orthogonal Transformation

To inspire project ideas, here are some cool Computer Vision papers:

• Object recognition: [Krizhevsky et al.], [Russakovsky et al.], [Szegedy et al.], [Simonyan et al.], [He et al.]
• Object detection: [Girshick et al.], [Sermanet et al.], [Erhan et al.]
• Image segmentation: [Long et al.]
• Video classification: [Karpathy et al.], [Simonyan and Zisserman]
• Scene classification: [Zhou et al.]
• Face recognition: [Taigman et al.]
• Depth estimation: [Eigen et al.]
• Image-to-sentence generation: [Karpathy and Fei-Fei], [Donahue et al.], [Vinyals et al.]
• Visualization and optimization: [Szegedy et al.], [Nguyen et al.], [Zeiler and Fergus], [Goodfellow et al.], [Schaul et al.]

Interesting datasets

NLP datasets:

• Sequence Tagging: Named Entity Recognition and Chunking
• Dependency Parsing
• Quora Question Pairs
• Sentence-Level Sentiment Analysis and Document-Level Sentiment Analysis
• Textual Entailment
• Machine Translation (Ambitious)
• Yelp Reviews
• WikiText Language Modeling
• Fake News Challenge
• Toxic Comment Classification

Computer vision datasets:

• Meta Pointer: A large collection organized by CV Datasets.
• Yet another Meta pointer
• ImageNet: a large-scale image dataset for visual recognition organized by WordNet hierarchy
• SUN Database: a benchmark for scene recognition and object detection with annotated scene categories and segmented objects
• Places Database: a scene-centric database with 205 scene categories and 2.5 millions of labelled images
• NYU Depth Dataset v2: a RGB-D dataset of segmented indoor scenes
• Microsoft COCO: a new benchmark for image recognition, segmentation and captioning
• Flickr100M: 100 million creative commons Flickr images
• Labeled Faces in the Wild: a dataset of 13,000 labeled face photographs
• Human Pose Dataset: a benchmark for articulated human pose estimation
• YouTube Faces DB: a face video dataset for unconstrained face recognition in videos
• UCF101: an action recognition data set of realistic action videos with 101 action categories
• HMDB-51: a large human motion dataset of 51 action classes

Others: you can always explore the Kaggle Datasets for various types of datasets.