Search Results for author:
Found 9 papers, 5 papers with code
CLoVe: Encoding Compositional Language in Contrastive Vision-Language Models
Recent years have witnessed a significant increase in the performance of Vision and Language tasks.
Video Annotator: A framework for efficiently building video classifiers using vision-language models and active learning
High-quality and consistent annotations are fundamental to the successful development of robust machine learning models.
RAFIC: Retrieval-Augmented Few-shot Image Classification
Few-shot image classification is the task of classifying unseen images to one of N mutually exclusive classes, using only a small number of training examples for each class.
Match Cutting: Finding Cuts with Smooth Visual Transitions
A match cut is a transition between a pair of shots that uses similar framing, composition, or action to fluidly bring the viewer from one scene to the next.
Abuse and Fraud Detection in Streaming Services Using Heuristic-Aware Machine Learning
We study the use of semi-supervised as well as supervised approaches for anomaly detection.
Detecting Kissing Scenes in a Database of Hollywood Films
We propose a system for detecting kissing scenes in a movie.
Mining Data from the Congressional Record
We propose a data storage and analysis method for using the US Congressional record as a policy analysis tool.
Compositional pre-training for neural semantic parsing
Semantic parsing is the process of translating natural language utterances into logical forms, which has many important applications such as question answering and instruction following.
Active Learning for Network Intrusion Detection
For most networks the vast majority of traffic is legitimate.
