3 citations · 8 across the 11 of their papers we have counts for
6 papers · 1 filter
Cinéaste: A Fine-grained Contextual Movie Question Answering Benchmark
Nisarg A. Shah, Amir Ziai, Chaitanya Ekanadham +1
While recent advancements in vision-language models have improved video understanding, diagnosing their capacity for deep, narrative comprehension remains a challenge. Existing ben…
CLoVe: Encoding Compositional Language in Contrastive Vision-Language Models
Santiago Castro, Amir Ziai, Avneesh Saluja +2
Recent years have witnessed a significant increase in the performance of Vision and Language tasks. Foundational Vision-Language Models (VLMs), such as CLIP, have been leveraged in…
Video Annotator: A framework for efficiently building video classifiers using vision-language models and active learning
Amir Ziai, Aneesh Vartakavi
High-quality and consistent annotations are fundamental to the successful development of robust machine learning models. Traditional data annotation methods are resource-intensive…
RAFIC: Retrieval-Augmented Few-shot Image Classification
Hangfei Lin, Li Miao, Amir Ziai
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. The li…
Match Cutting: Finding Cuts with Smooth Visual Transitions
Boris Chen, Amir Ziai, Rebecca Tucker +1
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. Match cuts are frequen…
Detecting Kissing Scenes in a Database of Hollywood Films
Amir Ziai
Detecting scene types in a movie can be very useful for application such as video editing, ratings assignment, and personalization. We propose a system for detecting kissing scenes…