7 citations · 18 across the 12 of their papers we have counts for
12 papers
Enhancing Generalization in Vision-Language-Action Models by Preserving Pretrained Representations
Shresth Grover, Akshay Gopalkrishnan, Bo Ai +3
Vision-language-action (VLA) models finetuned from vision-language models (VLMs) hold the promise of leveraging rich pretrained representations to build generalist robots across di…
Safety-Critical Learning for Long-Tail Events: The TUM Traffic Accident Dataset
Walter Zimmer, Ross Greer, Xingcheng Zhou +7
Even though a significant amount of work has been done to increase the safety of transportation networks, accidents still occur regularly. They must be understood as an unavoidable…
Towards Vision Zero: The TUM Traffic Accid3nD Dataset
Walter Zimmer, Ross Greer, Daniel Lehmberg +9
Even though a significant amount of work has been done to increase the safety of transportation networks, accidents still occur regularly. They must be understood as unavoidable an…
Enhancing Highway Safety: Accident Detection on the A9 Test Stretch Using Roadside Sensors
Walter Zimmer, Ross Greer, Xingcheng Zhou +7
Road traffic injuries are the leading cause of death for people aged 5-29, resulting in about 1.19 million deaths each year. To reduce these fatalities, it is essential to address…
Multi-Frame, Lightweight & Efficient Vision-Language Models for Question Answering in Autonomous Driving
Akshay Gopalkrishnan, Ross Greer, Mohan Trivedi
Vision-Language Models (VLMs) and Multi-Modal Language models (MMLMs) have become prominent in autonomous driving research, as these models can provide interpretable textual reason…
Vision-based Analysis of Driver Activity and Driving Performance Under the Influence of Alcohol
Ross Greer, Akshay Gopalkrishnan, Sumega Mandadi +3
About 30% of all traffic crash fatalities in the United States involve drunk drivers, making the prevention of drunk driving paramount to vehicle safety in the US and other locatio…
Robust Detection, Association, and Localization of Vehicle Lights: A Context-Based Cascaded CNN Approach and Evaluations
Akshay Gopalkrishnan, Ross Greer, Maitrayee Keskar +1
Vehicle light detection, association, and localization are required for important downstream safe autonomous driving tasks, such as predicting a vehicle's light state to determine…
Patterns of Vehicle Lights: Addressing Complexities in Curation and Annotation of Camera-Based Vehicle Light Datasets and Metrics
Ross Greer, Akshay Gopalkrishnan, Maitrayee Keskar +1
This paper explores the representation of vehicle lights in computer vision and its implications for various tasks in the field of autonomous driving. Different specifications for…
Robust Traffic Light Detection Using Salience-Sensitive Loss: Computational Framework and Evaluations
Ross Greer, Akshay Gopalkrishnan, Jacob Landgren +3
One of the most important tasks for ensuring safe autonomous driving systems is accurately detecting road traffic lights and accurately determining how they impact the driver's act…
Pedestrian Behavior Maps for Safety Advisories: CHAMP Framework and Real-World Data Analysis
Ross Greer, Samveed Desai, Lulua Rakla +3
It is critical for vehicles to prevent any collisions with pedestrians. Current methods for pedestrian collision prevention focus on integrating visual pedestrian detectors with Au…
CHAMP: Crowdsourced, History-Based Advisory of Mapped Pedestrians for Safer Driver Assistance Systems
Ross Greer, Lulua Rakla, Samveed Desai +3
Vehicles are constantly approaching and sharing the road with pedestrians, and as a result it is critical for vehicles to prevent any collisions with pedestrians. Current methods f…
Salient Sign Detection In Safe Autonomous Driving: AI Which Reasons Over Full Visual Context
Ross Greer, Akshay Gopalkrishnan, Nachiket Deo +2
Detecting road traffic signs and accurately determining how they can affect the driver's future actions is a critical task for safe autonomous driving systems. However, various tra…