32 citations · 108 across the 33 of their papers we have counts for
37 papers
Easy3D-Labels: Supervising Semantic Occupancy Estimation with 3D Pseudo-Labels for Automotive Perception
Seamie Hayes, Ganesh Sistu, Tim Brophy +1
In perception for automated vehicles, safety is critical not only for the driver but also for other agents in the scene, particularly vulnerable road users such as pedestrians and…
Revisiting Birds Eye View Perception Models with Frozen Foundation Models: DINOv2 and Metric3Dv2
Seamie Hayes, Ganesh Sistu, Ciarán Eising
Birds Eye View perception models require extensive data to perform and generalize effectively. While traditional datasets often provide abundant driving scenes from diverse locatio…
MapsTP: HD Map Images Based Multimodal Trajectory Prediction for Automated Vehicles
Sushil Sharma, Arindam Das, Ganesh Sistu +2
Predicting ego vehicle trajectories remains a critical challenge, especially in urban and dense areas due to the unpredictable behaviours of other vehicles and pedestrians. Multimo…
FisheyeDetNet: 360° Surround view Fisheye Camera based Object Detection System for Autonomous Driving
Ganesh Sistu, Senthil Yogamani
Object detection is a mature problem in autonomous driving with pedestrian detection being one of the first deployed algorithms. It has been comprehensively studied in the literatu…
Scalable and Efficient Hierarchical Visual Topological Mapping
Saravanabalagi Ramachandran, Jonathan Horgan, Ganesh Sistu +1
Hierarchical topological representations can significantly reduce search times within mapping and localization algorithms. Although recent research has shown the potential for such…
Fisheye Camera and Ultrasonic Sensor Fusion For Near-Field Obstacle Perception in Bird's-Eye-View
Arindam Das, Sudarshan Paul, Niko Scholz +4
Accurate obstacle identification represents a fundamental challenge within the scope of near-field perception for autonomous driving. Conventionally, fisheye cameras are frequently…
WoodScape Motion Segmentation for Autonomous Driving -- CVPR 2023 OmniCV Workshop Challenge
Saravanabalagi Ramachandran, Nathaniel Cibik, Ganesh Sistu +1
Motion segmentation is a complex yet indispensable task in autonomous driving. The challenges introduced by the ego-motion of the cameras, radial distortion in fisheye lenses, and…
Optimizing Ego Vehicle Trajectory Prediction: The Graph Enhancement Approach
Sushil Sharma, Aryan Singh, Ganesh Sistu +2
Predicting the trajectory of an ego vehicle is a critical component of autonomous driving systems. Current state-of-the-art methods typically rely on Deep Neural Networks (DNNs) an…
BEVSeg2TP: Surround View Camera Bird's-Eye-View Based Joint Vehicle Segmentation and Ego Vehicle Trajectory Prediction
Sushil Sharma, Arindam Das, Ganesh Sistu +2
Trajectory prediction is, naturally, a key task for vehicle autonomy. While the number of traffic rules is limited, the combinations and uncertainties associated with each agent's…
Self-Supervised Online Camera Calibration for Automated Driving and Parking Applications
Ciarán Hogan, Ganesh Sistu, Ciarán Eising
Camera-based perception systems play a central role in modern autonomous vehicles. These camera based perception algorithms require an accurate calibration to map the real world di…
Towards a performance analysis on pre-trained Visual Question Answering models for autonomous driving
Kaavya Rekanar, Ciarán Eising, Ganesh Sistu +1
This short paper presents a preliminary analysis of three popular Visual Question Answering (VQA) models, namely ViLBERT, ViLT, and LXMERT, in the context of answering questions re…
Navigating Uncertainty: The Role of Short-Term Trajectory Prediction in Autonomous Vehicle Safety
Sushil Sharma, Ganesh Sistu, Lucie Yahiaoui +3
Autonomous vehicles require accurate and reliable short-term trajectory predictions for safe and efficient driving. While most commercial automated vehicles currently use state mac…
Near Field iToF LIDAR Depth Improvement from Limited Number of Shots
Mena Nagiub, Thorsten Beuth, Ganesh Sistu +2
Indirect Time of Flight LiDARs can indirectly calculate the scene's depth from the phase shift angle between transmitted and received laser signals with amplitudes modulated at a p…
Revisiting Modality Imbalance In Multimodal Pedestrian Detection
Arindam Das, Sudip Das, Ganesh Sistu +5
Multimodal learning, particularly for pedestrian detection, has recently received emphasis due to its capability to function equally well in several critical autonomous driving sce…
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…
Woodscape Fisheye Object Detection for Autonomous Driving -- CVPR 2022 OmniCV Workshop Challenge
Saravanabalagi Ramachandran, Ganesh Sistu, Varun Ravi Kumar +2
Object detection is a comprehensively studied problem in autonomous driving. However, it has been relatively less explored in the case of fisheye cameras. The strong radial distort…
Deep Multi-Task Networks For Occluded Pedestrian Pose Estimation
Arindam Das, Sudip Das, Ganesh Sistu +5
Most of the existing works on pedestrian pose estimation do not consider estimating the pose of an occluded pedestrian, as the annotations of the occluded parts are not available i…
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…
FisheyeSuperPoint: Keypoint Detection and Description Network for Fisheye Images
Anna Konrad, Ciarán Eising, Ganesh Sistu +3
Keypoint detection and description is a commonly used building block in computer vision systems particularly for robotics and autonomous driving. However, the majority of technique…
Generalized Object Detection on Fisheye Cameras for Autonomous Driving: Dataset, Representations and Baseline
Hazem Rashed, Eslam Mohamed, Ganesh Sistu +4
Object detection is a comprehensively studied problem in autonomous driving. However, it has been relatively less explored in the case of fisheye cameras. The standard bounding box…
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…