1 citations · 3 across the 7 of their papers we have counts for
7 papers
Adapting Dual-encoder Vision-language Models for Paraphrased Retrieval
Jiacheng Cheng, Hijung Valentina Shin, Nuno Vasconcelos +2
In the recent years, the dual-encoder vision-language models (\eg CLIP) have achieved remarkable text-to-image retrieval performance. However, we discover that these models usually…
Concept Weaver: Enabling Multi-Concept Fusion in Text-to-Image Models
Gihyun Kwon, Simon Jenni, Dingzeyu Li +3
While there has been significant progress in customizing text-to-image generation models, generating images that combine multiple personalized concepts remains challenging. In this…
Towards Automated Movie Trailer Generation
Dawit Mureja Argaw, Mattia Soldan, Alejandro Pardo +4
Movie trailers are an essential tool for promoting films and attracting audiences. However, the process of creating trailers can be time-consuming and expensive. To streamline this…
Scaling Up Video Summarization Pretraining with Large Language Models
Dawit Mureja Argaw, Seunghyun Yoon, Fabian Caba Heilbron +5
Long-form video content constitutes a significant portion of internet traffic, making automated video summarization an essential research problem. However, existing video summariza…
Long-range Multimodal Pretraining for Movie Understanding
Dawit Mureja Argaw, Joon-Young Lee, Markus Woodson +2
Learning computer vision models from (and for) movies has a long-standing history. While great progress has been attained, there is still a need for a pretrained multimodal model t…
The Anatomy of Video Editing: A Dataset and Benchmark Suite for AI-Assisted Video Editing
Dawit Mureja Argaw, Fabian Caba Heilbron, Joon-Young Lee +2
Machine learning is transforming the video editing industry. Recent advances in computer vision have leveled-up video editing tasks such as intelligent reframing, rotoscoping, colo…