Hateful Memes dataset contains real hate speech. The Real Hateful Memes dataset consists of more than 10,000 newly created examples by Facebook AI.
-
Updated
May 17, 2021 - Jupyter Notebook
Hateful Memes dataset contains real hate speech. The Real Hateful Memes dataset consists of more than 10,000 newly created examples by Facebook AI.
Deepfake Detection Solution using Multimodal Approach.
Create a large, well-managed and clean data-set for the task of music composition for video soundtracks.
Analyzing Hateful Memes/ (Resources:- Hateful Memes Challenge)
Experiments around using Multi-Modal Casual Attention with Multi-Grouped Query Attention
Facebook Marketplace is a platform for buying and selling products on Facebook. This project involves training a multimodal deep neural network model that predicts the category of a product based on its image and text description.
A Fully Deployable React-Native mobile app that seeks to classify incoming messages in messaging apps into important or disturbing categories. using a Multi-Modal Machine Learning Architecture to achieve Text classification, Image classification and YouTube Video Link classification.
Multimodal Agentic GenAI Workflow – Seamlessly blends retrieval and generation for intelligent storytelling
A list of research papers on knowledge-enhanced multimodal learning
Multi-speaker diarization from video using SyncNet’s cross-modal embedding space to match multiple face tracks to corresponding audio tracks.
[IROS 2023] GVCCI: Lifelong Learning of Visual Grounding for Language-Guided Robotic Manipulation
Multimodal deep learning model for fake news classification.
App to cheer you up with some awesome quotes when depressed using deep learning
SIREN Scalable, Isotropic Recursive Column Multimodal Neural Architecture with Device State Recognition Use-Case
Example of a multimodal (end-to-end) deep learning model with transformers architecture
Image Recommendation for Wikipedia Articles
MSc project investigating multi-modal fusion approaches to combining textual and visual features for multi-page classification of documents within the OGA National Data Repository (NDR).
A PyTorch implementation of a Transformer Network for Machine Translation that incorporates image features to enhance the performance of the translation
Build a reliable and interpretable model that classifies extreme weather from images – enhancing early detection, situational awareness, and decision-making.
Add a description, image, and links to the multimodal-deep-learning topic page so that developers can more easily learn about it.
To associate your repository with the multimodal-deep-learning topic, visit your repo's landing page and select "manage topics."