138 citations · 179 across the 38 of their papers we have counts for
7 papers · 1 filter
PhysicsLENS: Diagnosing Physical Property Blindness in Video Generation Models
Isaiah Milkey, Som Sagar, Aditya Taparia +3
Reliable video world models could provide scalable predictive environments for robot learning, planning, and evaluation. However, generated robot videos can violate physical princi…
VLC Fusion: Vision-Language Conditioned Sensor Fusion for Robust Object Detection
Aditya Taparia, Noel Ngu, Mario Leiva +6
Although fusing multiple sensor modalities can enhance object detection performance, existing fusion approaches often overlook subtle variations in environmental conditions and sen…
Explainable Concept Generation through Vision-Language Preference Learning for Understanding Neural Networks' Internal Representations
Aditya Taparia, Som Sagar, Ransalu Senanayake
Understanding the inner representation of a neural network helps users improve models. Concept-based methods have become a popular choice for explaining deep neural networks post-h…
Fairness in Autonomous Driving: Towards Understanding Confounding Factors in Object Detection under Challenging Weather
Bimsara Pathiraja, Caleb Liu, Ransalu Senanayake
The deployment of autonomous vehicles (AVs) is rapidly expanding to numerous cities. At the heart of AVs, the object detection module assumes a paramount role, directly influencing…
Out of Distribution Detection and Adversarial Attacks on Deep Neural Networks for Robust Medical Image Analysis
Anisie Uwimana1, Ransalu Senanayake
Deep learning models have become a popular choice for medical image analysis. However, the poor generalization performance of deep learning models limits them from being deployed i…
Out-of-Distribution Detection for Automotive Perception
Julia Nitsch, Masha Itkina, Ransalu Senanayake +5
Neural networks (NNs) are widely used for object classification in autonomous driving. However, NNs can fail on input data not well represented by the training dataset, known as ou…
Online Domain Adaptation for Occupancy Mapping
Anthony Tompkins, Ransalu Senanayake, Fabio Ramos
Creating accurate spatial representations that take into account uncertainty is critical for autonomous robots to safely navigate in unstructured environments. Although recent LIDA…