This repo contains annotated research papers. These notes/annotations were prepared using Logseq.

Computer Vision

Large CNNs for Image Classification

• ImageNet Classification with Deep Convolutional Neural Networks [Paper]
• Spatial Transformer Networks [Paper]

Transformers in Computer Vision

• An Image is 16x16 words: Transformers for Image Recognition at Scale [Paper]
• MLP-Mixer: An all-MLP Architecture for Vision [Paper]
• Swin Transformer: Hierarchical Vision Transformer using Shifted Windows [Paper]

Object Detection

• You Only Look Once: Unified, Real-Time Object Detection [Paper]
• YOLO9000: Better, Faster, Stronger [Paper]
• Focal Loss for Dense Object Detection [Paper]

Face Recognition

• DeepFace: Closing the Gap to Human- Level Performance in Face Verification [Paper]
• FaceNet: A Unified Embedding for Face Recognition and Clustering [Paper]
• A Discriminative Feature Learning Approach for Deep Face Recognition [Paper]

Explainability/Visualizing in Computer Vision

• Learning Deep Features for Discriminative Localization [Paper]
• Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization [Paper]

Self-Supervised Learning

• Momentum Contrast for Unsupervised Visual Representation Learning [Paper]

Natural Language Processing

Word Representations

• Distributed Representations of Words and Phrases and their Compositionality [Paper]
• Efficient Estimation of Word Representations in Vector Space [Paper]

Machine Translation

• Attention Is All You Need [Paper]

Knowledge Distillation

• Distilling the Knowledge in a Neural Network [Paper]