18 citations · 22 across the 9 of their papers we have counts for
12 papers
Personalized LLM Recommendation with Semantic IDs: Autoregressive Beam Search vs. Multi-Token Prediction
Sejoon Oh, Fernando Amat Gil, Evan Smothers +11
Large-scale personalization is shifting from embedding-table retrieval to LLM-based recommenders that generate the Semantic ID (SID) of the item to recommend, where each SID is a s…
MambaVideo for Discrete Video Tokenization with Channel-Split Quantization
Dawit Mureja Argaw, Xian Liu, Joon Son Chung +2
Discrete video tokenization is essential for efficient autoregressive generative modeling due to the high dimensionality of video data. This work introduces a state-of-the-art disc…
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…
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…
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…
Long-term Video Frame Interpolation via Feature Propagation
Dawit Mureja Argaw, In So Kweon
Video frame interpolation (VFI) works generally predict intermediate frame(s) by first estimating the motion between inputs and then warping the inputs to the target time with the…
Restoration of Video Frames from a Single Blurred Image with Motion Understanding
Dawit Mureja Argaw, Junsik Kim, Francois Rameau +2
We propose a novel framework to generate clean video frames from a single motion-blurred image. While a broad range of literature focuses on recovering a single image from a blurre…
Optical Flow Estimation from a Single Motion-blurred Image
Dawit Mureja Argaw, Junsik Kim, Francois Rameau +2
In most of computer vision applications, motion blur is regarded as an undesirable artifact. However, it has been shown that motion blur in an image may have practical interests in…
Motion-blurred Video Interpolation and Extrapolation
Dawit Mureja Argaw, Junsik Kim, Francois Rameau +1
Abrupt motion of camera or objects in a scene result in a blurry video, and therefore recovering high quality video requires two types of enhancements: visual enhancement and tempo…
ResNet or DenseNet? Introducing Dense Shortcuts to ResNet
Chaoning Zhang, Philipp Benz, Dawit Mureja Argaw +5
ResNet or DenseNet? Nowadays, most deep learning based approaches are implemented with seminal backbone networks, among them the two arguably most famous ones are ResNet and DenseN…