7 papers
THYME: Temporal Hierarchical-Cyclic Interactivity Modeling for Video Scene Graphs in Aerial Footage
Trong-Thuan Nguyen, Pha Nguyen, Jackson Cothren +3
The rapid proliferation of video in applications such as autonomous driving, surveillance, and sports analytics necessitates robust methods for dynamic scene understanding. Despite…
HyperGLM: HyperGraph for Video Scene Graph Generation and Anticipation
Trong-Thuan Nguyen, Pha Nguyen, Jackson Cothren +2
Multimodal LLMs have advanced vision-language tasks but still struggle with understanding video scenes. To bridge this gap, Video Scene Graph Generation (VidSGG) has emerged to cap…
DEFEND: A Large-scale 1M Dataset and Foundation Model for Tobacco Addiction Prevention
Naga VS Raviteja Chappa, Matthew Shepard, Connor McCurtain +3
While tobacco advertising innovates at unprecedented speed, traditional surveillance methods remain frozen in time, especially in the context of social media. The lack of large-sca…
LiGAR: LiDAR-Guided Hierarchical Transformer for Multi-Modal Group Activity Recognition
Naga Venkata Sai Raviteja Chappa, Khoa Luu
Group Activity Recognition (GAR) remains challenging in computer vision due to the complex nature of multi-agent interactions. This paper introduces LiGAR, a LIDAR-Guided Hierarchi…
FLAASH: Flow-Attention Adaptive Semantic Hierarchical Fusion for Multi-Modal Tobacco Content Analysis
Naga VS Raviteja Chappa, Page Daniel Dobbs, Bhiksha Raj +1
The proliferation of tobacco-related content on social media platforms poses significant challenges for public health monitoring and intervention. This paper introduces a novel mul…
Public Health Advocacy Dataset: A Dataset of Tobacco Usage Videos from Social Media
Naga VS Raviteja Chappa, Charlotte McCormick, Susana Rodriguez Gongora +2
The Public Health Advocacy Dataset (PHAD) is a comprehensive collection of 5,730 videos related to tobacco products sourced from social media platforms like TikTok and YouTube. Thi…