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Found 13 papers, 4 papers with code
Towards Child-Inclusive Clinical Video Understanding for Autism Spectrum Disorder
Objective analyses of these videos could provide clinicians and researchers with nuanced insights into the behavior of children with Autism Spectrum Disorder.
Can Text-to-image Model Assist Multi-modal Learning for Visual Recognition with Visual Modality Missing?
Specifically, we propose a simple but effective multi-modal learning framework GTI-MM to enhance the data efficiency and model robustness against missing visual modality by imputing the missing data with generative transformers.
Does Video Summarization Require Videos? Quantifying the Effectiveness of Language in Video Summarization
Video summarization remains a huge challenge in computer vision due to the size of the input videos to be summarized.
MM-AU:Towards Multimodal Understanding of Advertisement Videos
Advertisement videos (ads) play an integral part in the domain of Internet e-commerce as they amplify the reach of particular products to a broad audience or can serve as a medium to raise awareness about specific issues through concise narrative structures.
FedMultimodal: A Benchmark For Multimodal Federated Learning
In order to facilitate the research in multimodal FL, we introduce FedMultimodal, the first FL benchmark for multimodal learning covering five representative multimodal applications from ten commonly used datasets with a total of eight unique modalities.
Signal Processing Grand Challenge 2023 -- e-Prevention: Sleep Behavior as an Indicator of Relapses in Psychotic Patients
This paper presents the approach and results of USC SAIL's submission to the Signal Processing Grand Challenge 2023 - e-Prevention (Task 2), on detecting relapses in psychotic patients.
Contextually-rich human affect perception using multimodal scene information
The process of human affect understanding involves the ability to infer person specific emotional states from various sources including images, speech, and language.
A dataset for Audio-Visual Sound Event Detection in Movies
In this work, we present a dataset of audio events called Subtitle-Aligned Movie Sounds (SAM-S).
Multimodal Estimation of Change Points of Physiological Arousal in Drivers
Detecting unsafe driving states, such as stress, drowsiness, and fatigue, is an important component of ensuring driving safety and an essential prerequisite for automatic intervention systems in vehicles.
MovieCLIP: Visual Scene Recognition in Movies
Longform media such as movies have complex narrative structures, with events spanning a rich variety of ambient visual scenes.
Understanding of Emotion Perception from Art
Computational modeling of the emotions evoked by art in humans is a challenging problem because of the subjective and nuanced nature of art and affective signals.
Cross Domain Emotion Recognition using Few Shot Knowledge Transfer
Emotion recognition from text is a challenging task due to diverse emotion taxonomies, lack of reliable labeled data in different domains, and highly subjective annotation standards.
Clustering using Vector Membership: An Extension of the Fuzzy C-Means Algorithm
We also examine the efficacy of the proposed scheme by analyzing its performance on image segmentation examples and comparing it with the classical Fuzzy C-means clustering algorithm.
