27 citations · 43 across the 8 of their papers we have counts for
9 papers
Video-based Music Generation
Serkan Sulun
As the volume of video content on the internet grows rapidly, finding a suitable soundtrack remains a significant challenge. This thesis presents EMSYNC (EMotion and SYNChronizatio…
Video Soundtrack Generation by Aligning Emotions and Temporal Boundaries
Serkan Sulun, Paula Viana, Matthew E. P. Davies
Providing soundtracks for videos remains a costly and time-consuming challenge for multimedia content creators. We introduce EMSYNC, an automatic video-based symbolic music generat…
VEMOCLAP: A video emotion classification web application
Serkan Sulun, Paula Viana, Matthew E. P. Davies
We introduce VEMOCLAP: Video EMOtion Classifier using Pretrained features, the first readily available and open-source web application that analyzes the emotional content of any us…
Movie Trailer Genre Classification Using Multimodal Pretrained Features
Serkan Sulun, Paula Viana, Matthew E. P. Davies
We introduce a novel method for movie genre classification, capitalizing on a diverse set of readily accessible pretrained models. These models extract high-level features related…
Emotion4MIDI: a Lyrics-based Emotion-Labeled Symbolic Music Dataset
Serkan Sulun, Pedro Oliveira, Paula Viana
We present a new large-scale emotion-labeled symbolic music dataset consisting of 12k MIDI songs. To create this dataset, we first trained emotion classification models on the GoEm…
Symbolic music generation conditioned on continuous-valued emotions
Serkan Sulun, Matthew E. P. Davies, Paula Viana
In this paper we present a new approach for the generation of multi-instrument symbolic music driven by musical emotion. The principal novelty of our approach centres on conditioni…
On Filter Generalization for Music Bandwidth Extension Using Deep Neural Networks
Serkan Sulun, Matthew E. P. Davies
In this paper, we address a sub-topic of the broad domain of audio enhancement, namely musical audio bandwidth extension. We formulate the bandwidth extension problem using deep ne…
Can Learned Frame-Prediction Compete with Block-Motion Compensation for Video Coding?
Serkan Sulun, A. Murat Tekalp
Given recent advances in learned video prediction, we investigate whether a simple video codec using a pre-trained deep model for next frame prediction based on previously encoded/…
Deep Learned Frame Prediction for Video Compression
Serkan Sulun
Motion compensation is one of the most essential methods for any video compression algorithm. Video frame prediction is a task analogous to motion compensation. In recent years, th…