activity
20222024
most citedBlurry Video Compression: A Trade-off between Visual Enhancement and Data Compression

1 citations · 3 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2024

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…

cs.CV20241 cited

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…

eess.IV20231 cited

Blurry Video Compression: A Trade-off between Visual Enhancement and Data Compression

Dawit Mureja Argaw, Junsik Kim, In So Kweon

Existing video compression (VC) methods primarily aim to reduce the spatial and temporal redundancies between consecutive frames in a video while preserving its quality. In this re…

cs.CV20231 cited

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…

cs.CV2022

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…