7 papers · 1 filter
Probing Visual Concepts in Lightweight Vision-Language Models for Automated Driving
Nikos Theodoridis, Reenu Mohandas, Ganesh Sistu +3
The use of Vision-Language Models (VLMs) in automated driving applications is becoming increasingly common, with the aim of leveraging their reasoning and generalisation capabiliti…
SuperQuadricOcc: Real-Time Self-Supervised Semantic Occupancy Estimation with Superquadric Volume Rendering
Seamie Hayes, Alexandre Boulch, Andrei Bursuc +4
Self-supervision for semantic occupancy estimation is appealing as it removes the labour-intensive manual annotation, thus allowing one to scale to larger autonomous driving datase…
Descriptor: Distance-Annotated Traffic Perception Question Answering (DTPQA)
Nikos Theodoridis, Tim Brophy, Reenu Mohandas +4
The remarkable progress of Vision-Language Models (VLMs) on a variety of tasks has raised interest in their application to automated driving. However, for these models to be truste…
Evaluating Small Vision-Language Models on Distance-Dependent Traffic Perception
Nikos Theodoridis, Tim Brophy, Reenu Mohandas +4
Vision-Language Models (VLMs) are becoming increasingly powerful, demonstrating strong performance on a variety of tasks that require both visual and textual understanding. Their s…
FIN: Fast Inference Network for Map Segmentation
Ruan Bispo, Tim Brophy, Reenu Mohandas +2
Multi-sensor fusion in autonomous vehicles is becoming more common to offer a more robust alternative for several perception tasks. This need arises from the unique contribution of…
Deformable Convolution Based Road Scene Semantic Segmentation of Fisheye Images in Autonomous Driving
Anam Manzoor, Aryan Singh, Ganesh Sistu +4
This study investigates the effectiveness of modern Deformable Convolutional Neural Networks (DCNNs) for semantic segmentation tasks, particularly in autonomous driving scenarios w…