Genre classification
46 papers with code • 2 benchmarks • 6 datasets
Genre classification is the process of grouping objects together based on defined similarities such as shape, pixel, location, or intensity.
FMA
MuMu
Moviescope
Trailers12k
PTVD
Latest papers with no code
Music Genre Classification: A Comparative Analysis of CNN and XGBoost Approaches with Mel-frequency cepstral coefficients and Mel Spectrograms
The effectiveness of systems largely depends on feature and model selection, as different architectures and features can facilitate each other and yield different results.
Panel Transitions for Genre Analysis in Visual Narratives
Our contributions to the community are: a dataset of annotated manga books, a multi-modal analysis of visual panels and text in a constrained and popular medium through high-level features, and a systematic process for incorporating subjective narrative patterns in computational models.
Towards Automated Recipe Genre Classification using Semi-Supervised Learning
Sharing cooking recipes is a great way to exchange culinary ideas and provide instructions for food preparation.
Exploring Music Genre Classification: Algorithm Analysis and Deployment Architecture
The proposed DSP and DL-based music genre classification algorithm and deployment architecture demonstrate a promising approach for music genre classification.
Towards Contrastive Learning in Music Video Domain
To gain a better understanding of the reasons contrastive learning was not successful for music videos, we perform a qualitative analysis of the learned representations, revealing why contrastive learning might have difficulties uniting embeddings from two modalities.
Music Genre Classification with ResNet and Bi-GRU Using Visual Spectrograms
Music recommendation systems have emerged as a vital component to enhance user experience and satisfaction for the music streaming services, which dominates music consumption.
Modality Influence in Multimodal Machine Learning
This paper aims to address this gap by studying the impact of each modality on multimodal learning tasks.
Assorted, Archetypal and Annotated Two Million (3A2M) Cooking Recipes Dataset based on Active Learning
In this study, we present a novel dataset of two million culinary recipes labeled in respective categories leveraging the knowledge of food experts and an active learning technique.
GTR-CTRL: Instrument and Genre Conditioning for Guitar-Focused Music Generation with Transformers
We trained a BERT model for downstream genre classification and used it to assess the results obtained with the genre-CTRL model.
Convolution channel separation and frequency sub-bands aggregation for music genre classification
In music, short-term features such as pitch and tempo constitute long-term semantic features such as melody and narrative.
