Search Results for author: Ferda Ofli

Found 28 papers, 8 papers with code

Learning Program Representations for Food Images and Cooking Recipes

no code implementations CVPR 2022 Dim P. Papadopoulos, Enrique Mora, Nadiia Chepurko, Kuan Wei Huang, Ferda Ofli, Antonio Torralba

To validate our idea, we crowdsource programs for cooking recipes and show that: (a) projecting the image-recipe embeddings into programs leads to better cross-modal retrieval results; (b) generating programs from images leads to better recognition results compared to predicting raw cooking instructions; and (c) we can generate food images by manipulating programs via optimizing the latent code of a GAN.

Cross-Modal Retrieval

A Real-time System for Detecting Landslide Reports on Social Media using Artificial Intelligence

no code implementations14 Feb 2022 Ferda Ofli, Umair Qazi, Muhammad Imran, Julien Roch, Catherine Pennington, Vanessa Banks, Remy Bossu

This paper presents an online system that leverages social media data in real time to identify landslide-related information automatically using state-of-the-art artificial intelligence techniques.

Decision Making

Incidents1M: a large-scale dataset of images with natural disasters, damage, and incidents

1 code implementation11 Jan 2022 Ethan Weber, Dim P. Papadopoulos, Agata Lapedriza, Ferda Ofli, Muhammad Imran, Antonio Torralba

In this work, we present the Incidents1M Dataset, a large-scale multi-label dataset which contains 977, 088 images, with 43 incident and 49 place categories.

Humanitarian

Fight Detection from Still Images in the Wild

1 code implementation16 Nov 2021 Şeymanur Aktı, Ferda Ofli, Muhammad Imran, Hazim Kemal Ekenel

We also propose a new dataset, named Social Media Fight Images (SMFI), comprising real-world images of fight actions.

TBCOV: Two Billion Multilingual COVID-19 Tweets with Sentiment, Entity, Geo, and Gender Labels

1 code implementation4 Oct 2021 Muhammad Imran, Umair Qazi, Ferda Ofli

The widespread usage of social networks during mass convergence events, such as health emergencies and disease outbreaks, provides instant access to citizen-generated data that carry rich information about public opinions, sentiments, urgent needs, and situational reports.

Misinformation

Landslide Detection in Real-Time Social Media Image Streams

no code implementations3 Oct 2021 Ferda Ofli, Muhammad Imran, Umair Qazi, Julien Roch, Catherine Pennington, Vanessa J. Banks, Remy Bossu

Lack of global data inventories obstructs scientific modeling of and response to landslide hazards which are oftentimes deadly and costly.

Disaster Response Management

Mapping Vulnerable Populations with AI

no code implementations29 Jul 2021 Benjamin Kellenberger, John E. Vargas-Muñoz, Devis Tuia, Rodrigo C. Daudt, Konrad Schindler, Thao T-T Whelan, Brenda Ayo, Ferda Ofli, Muhammad Imran

Building functions shall be retrieved by parsing social media data like for instance tweets, as well as ground-based imagery, to automatically identify different buildings functions and retrieve further information such as the number of building stories.

Humanitarian Image Segmentation +1

Robust Training of Social Media Image Classification Models for Rapid Disaster Response

no code implementations9 Apr 2021 Firoj Alam, Tanvirul Alam, Muhammad Imran, Ferda Ofli

Images shared on social media help crisis managers gain situational awareness and assess incurred damages, among other response tasks.

Data Augmentation Disaster Response +3

HumAID: Human-Annotated Disaster Incidents Data from Twitter with Deep Learning Benchmarks

no code implementations7 Apr 2021 Firoj Alam, Umair Qazi, Muhammad Imran, Ferda Ofli

Social networks are widely used for information consumption and dissemination, especially during time-critical events such as natural disasters.

Decision Making

Deep Learning Benchmarks and Datasets for Social Media Image Classification for Disaster Response

no code implementations17 Nov 2020 Firoj Alam, Ferda Ofli, Muhammad Imran, Tanvirul Alam, Umair Qazi

In this study, we propose new datasets for disaster type detection, and informativeness classification, and damage severity assessment.

Disaster Response General Classification +3

Detecting natural disasters, damage, and incidents in the wild

1 code implementation ECCV 2020 Ethan Weber, Nuria Marzo, Dim P. Papadopoulos, Aritro Biswas, Agata Lapedriza, Ferda Ofli, Muhammad Imran, Antonio Torralba

While most studies on social media are limited to text, images offer more information for understanding disaster and incident scenes.

GeoCoV19: A Dataset of Hundreds of Millions of Multilingual COVID-19 Tweets with Location Information

1 code implementation22 May 2020 Umair Qazi, Muhammad Imran, Ferda Ofli

The past several years have witnessed a huge surge in the use of social media platforms during mass convergence events such as health emergencies, natural or human-induced disasters.

CrisisBench: Benchmarking Crisis-related Social Media Datasets for Humanitarian Information Processing

no code implementations14 Apr 2020 Firoj Alam, Hassan Sajjad, Muhammad Imran, Ferda Ofli

Time-critical analysis of social media streams is important for humanitarian organizations for planing rapid response during disasters.

General Classification Humanitarian +1

Rapid Damage Assessment Using Social Media Images by Combining Human and Machine Intelligence

no code implementations14 Apr 2020 Muhammad Imran, Firoj Alam, Umair Qazi, Steve Peterson, Ferda Ofli

Rapid damage assessment is one of the core tasks that response organizations perform at the onset of a disaster to understand the scale of damage to infrastructures such as roads, bridges, and buildings.

How to make a pizza: Learning a compositional layer-based GAN model

no code implementations CVPR 2019 Dim P. Papadopoulos, Youssef Tamaazousti, Ferda Ofli, Ingmar Weber, Antonio Torralba

From a visual perspective, every instruction step can be seen as a way to change the visual appearance of the dish by adding extra objects (e. g., adding an ingredient) or changing the appearance of the existing ones (e. g., cooking the dish).

Recipe1M+: A Dataset for Learning Cross-Modal Embeddings for Cooking Recipes and Food Images

no code implementations14 Oct 2018 Javier Marin, Aritro Biswas, Ferda Ofli, Nicholas Hynes, Amaia Salvador, Yusuf Aytar, Ingmar Weber, Antonio Torralba

In this paper, we introduce Recipe1M+, a new large-scale, structured corpus of over one million cooking recipes and 13 million food images.

General Classification

CrisisMMD: Multimodal Twitter Datasets from Natural Disasters

2 code implementations2 May 2018 Firoj Alam, Ferda Ofli, Muhammad Imran

Despite extensive research that mainly focuses on textual content to extract useful information, limited work has focused on the use of imagery content or the combination of both content types.

Social and Information Networks Computers and Society

Automatic Image Filtering on Social Networks Using Deep Learning and Perceptual Hashing During Crises

no code implementations9 Apr 2017 Dat Tien Nguyen, Firoj Alam, Ferda Ofli, Muhammad Imran

The extensive use of social media platforms, especially during disasters, creates unique opportunities for humanitarian organizations to gain situational awareness and launch relief operations accordingly.

Humanitarian

Face-to-BMI: Using Computer Vision to Infer Body Mass Index on Social Media

no code implementations9 Mar 2017 Enes Kocabey, Mustafa Camurcu, Ferda Ofli, Yusuf Aytar, Javier Marin, Antonio Torralba, Ingmar Weber

A person's weight status can have profound implications on their life, ranging from mental health, to longevity, to financial income.

Is Saki #delicious? The Food Perception Gap on Instagram and Its Relation to Health

no code implementations21 Feb 2017 Ferda Ofli, Yusuf Aytar, Ingmar Weber, Raggi al Hammouri, Antonio Torralba

Studying how food is perceived in relation to what it actually is typically involves a laboratory setup.

Remote Health Coaching System and Human Motion Data Analysis for Physical Therapy with Microsoft Kinect

no code implementations21 Dec 2015 Qifei Wang, Gregorij Kurillo, Ferda Ofli, Ruzena Bajcsy

In order to generate the kinematic parameter from the noisy data captured by Kinect, we propose a kinematic filtering algorithm based on Unscented Kalman Filter and the kinematic model of human skeleton.

Evaluation of Pose Tracking Accuracy in the First and Second Generations of Microsoft Kinect

no code implementations13 Dec 2015 Qifei Wang, Gregorij Kurillo, Ferda Ofli, Ruzena Bajcsy

Microsoft Kinect camera and its skeletal tracking capabilities have been embraced by many researchers and commercial developers in various applications of real-time human movement analysis.

Pose Tracking

Unsupervised Temporal Segmentation of Repetitive Human Actions Based on Kinematic Modeling and Frequency Analysis

no code implementations13 Dec 2015 Qifei Wang, Gregorij Kurillo, Ferda Ofli, Ruzena Bajcsy

In this paper, we propose a method for temporal segmentation of human repetitive actions based on frequency analysis of kinematic parameters, zero-velocity crossing detection, and adaptive k-means clustering.

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