3 citations · 4 across the 12 of their papers we have counts for
11 papers · 1 filter
Towards Driver Behavior Understanding: Weakly-Supervised Risk Perception in Driving Scenes
Nakul Agarwal, Yi-Ting Chen, Behzad Dariush
Achieving zero-collision mobility remains a key objective for intelligent vehicle systems, which requires understanding driver risk perception-a complex cognitive process shaped by…
Task-Aware Resolution Optimization for Visual Large Language Models
Weiqing Luo, Zhen Tan, Yifan Li +4
Real-world vision-language applications demand varying levels of perceptual granularity. However, most existing visual large language models (VLLMs), such as LLaVA, pre-assume a fi…
Pose-Aware Weakly-Supervised Action Segmentation
Seth Z. Zhao, Reza Ghoddoosian, Isht Dwivedi +2
Understanding human behavior is an important problem in the pursuit of visual intelligence. A challenge in this endeavor is the extensive and costly effort required to accurately l…
Follow the Rules: Reasoning for Video Anomaly Detection with Large Language Models
Yuchen Yang, Kwonjoon Lee, Behzad Dariush +2
Video Anomaly Detection (VAD) is crucial for applications such as security surveillance and autonomous driving. However, existing VAD methods provide little rationale behind detect…
Rank2Tell: A Multimodal Driving Dataset for Joint Importance Ranking and Reasoning
Enna Sachdeva, Nakul Agarwal, Suhas Chundi +5
The widespread adoption of commercial autonomous vehicles (AVs) and advanced driver assistance systems (ADAS) may largely depend on their acceptance by society, for which their per…
Weakly-Supervised Online Action Segmentation in Multi-View Instructional Videos
Reza Ghoddoosian, Isht Dwivedi, Nakul Agarwal +2
This paper addresses a new problem of weakly-supervised online action segmentation in instructional videos. We present a framework to segment streaming videos online at test time u…