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Found 18 papers, 3 papers with code
Surround-View Fisheye Optics in Computer Vision and Simulation: Survey and Challenges
Overall, this paper highlights the optical aberrations in automotive fisheye datasets, and the limitations of optical reality in simulated fisheye datasets, with a focus on computer vision in surround-view optical systems.
Fisheye Camera and Ultrasonic Sensor Fusion For Near-Field Obstacle Perception in Bird's-Eye-View
Therefore, we present, to our knowledge, the first end-to-end multimodal fusion model tailored for efficient obstacle perception in a bird's-eye-view (BEV) perspective, utilizing fisheye cameras and ultrasonic sensors.
Measuring Natural Scenes SFR of Automotive Fisheye Cameras
The Modulation Transfer Function (MTF) is an important image quality metric typically used in the automotive domain.
BEVSeg2TP: Surround View Camera Bird's-Eye-View Based Joint Vehicle Segmentation and Ego Vehicle Trajectory Prediction
The proposed method in this paper predicts trajectories by considering perception and trajectory prediction as a unified system.
Optimizing Ego Vehicle Trajectory Prediction: The Graph Enhancement Approach
Predicting the trajectory of an ego vehicle is a critical component of autonomous driving systems.
Connecting the Dots: Graph Neural Network Powered Ensemble and Classification of Medical Images
Deep learning models have demonstrated remarkable results for various computer vision tasks, including the realm of medical imaging.
Self-Supervised Online Camera Calibration for Automated Driving and Parking Applications
The framework is self-supervised and doesn't require any labelling or supervision to learn the calibration parameters.
Hardware Accelerators in Autonomous Driving
Computing platforms in autonomous vehicles record large amounts of data from many sensors, process the data through machine learning models, and make decisions to ensure the vehicle's safe operation.
Compact & Capable: Harnessing Graph Neural Networks and Edge Convolution for Medical Image Classification
In this study, we investigate the potential of Graph Neural Networks (GNNs) for medical image classification.
Towards a performance analysis on pre-trained Visual Question Answering models for autonomous driving
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 relating to driving scenarios.
Navigating Uncertainty: The Role of Short-Term Trajectory Prediction in Autonomous Vehicle Safety
To address this limitation, we have developed a synthetic dataset for short-term trajectory prediction tasks using the CARLA simulator.
Near Field iToF LIDAR Depth Improvement from Limited Number of Shots
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 predefined frequency.
Revisiting Modality Imbalance In Multimodal Pedestrian Detection
Multimodal learning, particularly for pedestrian detection, has recently received emphasis due to its capability to function equally well in several critical autonomous driving scenarios such as low-light, night-time, and adverse weather conditions.
Classification of electromagnetic interference induced image noise in an analog video link
Here, we propose a solution using deep learning models that analyse, and grade video content derived from an EMI compliance test.
Deep Multi-Task Networks For Occluded Pedestrian Pose Estimation
The proposed framework has improved state-of-the-art performances of pose estimation, pedestrian detection, and instance segmentation.
Ranked #18 on
Pose Estimation
on COCO test-dev
Direct Triangulation with Spherical Projection for Omnidirectional Cameras
In this paper, it is proposed to solve the problem of triangulation for calibrated omnidirectional cameras through the optimisation of ray-pairs on the projective sphere.
A 2.5D Vehicle Odometry Estimation for Vision Applications
This paper proposes a method to estimate the pose of a sensor mounted on a vehicle as the vehicle moves through the world, an important topic for autonomous driving systems.
FisheyeSuperPoint: Keypoint Detection and Description Network for Fisheye Images
Keypoint detection and description is a commonly used building block in computer vision systems particularly for robotics and autonomous driving.
