32 citations · 78 across the 11 of their papers we have counts for
17 papers
Fast and Efficient Scene Categorization for Autonomous Driving using VAEs
Saravanabalagi Ramachandran, Jonathan Horgan, Ganesh Sistu +1
Scene categorization is a useful precursor task that provides prior knowledge for many advanced computer vision tasks with a broad range of applications in content-based image inde…
ViT-BEVSeg: A Hierarchical Transformer Network for Monocular Birds-Eye-View Segmentation
Pramit Dutta, Ganesh Sistu, Senthil Yogamani +2
Generating a detailed near-field perceptual model of the environment is an important and challenging problem in both self-driving vehicles and autonomous mobile robotics. A Bird Ey…
Neuroevolutionary Multi-objective approaches to Trajectory Prediction in Autonomous Vehicles
Fergal Stapleton, Edgar Galván, Ganesh Sistu +1
The incentive for using Evolutionary Algorithms (EAs) for the automated optimization and training of deep neural networks (DNNs), a process referred to as neuroevolution, has gaine…
Woodscape Fisheye Semantic Segmentation for Autonomous Driving -- CVPR 2021 OmniCV Workshop Challenge
Saravanabalagi Ramachandran, Ganesh Sistu, John McDonald +1
We present the WoodScape fisheye semantic segmentation challenge for autonomous driving which was held as part of the CVPR 2021 Workshop on Omnidirectional Computer Vision (OmniCV)…
Ensemble-based Semi-supervised Learning to Improve Noisy Soiling Annotations in Autonomous Driving
Michal Uricar, Ganesh Sistu, Lucie Yahiaoui +1
Manual annotation of soiling on surround view cameras is a very challenging and expensive task. The unclear boundary for various soiling categories like water drops or mud particle…
Learning Panoptic Segmentation from Instance Contours
Sumanth Chennupati, Venkatraman Narayanan, Ganesh Sistu +2
Panoptic Segmentation aims to provide an understanding of background (stuff) and instances of objects (things) at a pixel level. It combines the separate tasks of semantic segmenta…