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Found 20 papers, 3 papers with code
Signing Avatar Performance Evaluation within EASIER Project
One major goal of the project is the direct involvement of sign language (SL) users at every stage of development of the project’s signing avatar.
A Novel Approach to Managing Lower Face Complexity in Signing Avatars
An avatar that produces legible, easy-to-understand signing is one of the essential components to an effective automatic signed/spoken translation system.
Supporting Mouthing in Signed Languages: New innovations and a proposal for future corpus building
This paper describes efforts to improve avatar mouthing by addressing these challenges, resulting in a new approach for mouthing animation.
Representation and Synthesis of Geometric Relocations
One of the key features of signed discourse is the geometric placements of gestural units in signing space.
Scalable and Efficient Hierarchical Visual Topological Mapping
Based on our empirical analysis of multiple runs, we identify that continuity and distinctiveness are crucial characteristics for an optimal global descriptor that enable efficient and scalable hierarchical mapping, and present a methodology for quantifying and contrasting these characteristics across different global descriptors.
WoodScape Motion Segmentation for Autonomous Driving -- CVPR 2023 OmniCV Workshop Challenge
Motion segmentation is a complex yet indispensable task in autonomous driving.
Fast and Efficient Scene Categorization for Autonomous Driving using VAEs
We train a Variational Autoencoder in an unsupervised manner and map images to a constrained multi-dimensional latent space and use the latent vectors as compact embeddings that serve as global descriptors for images.
GP-net: Flexible Viewpoint Grasp Proposal
We present the Grasp Proposal Network (GP-net), a Convolutional Neural Network model which can generate 6-DoF grasps from flexible viewpoints, e. g. as experienced by mobile manipulators.
Woodscape Fisheye Object Detection for Autonomous Driving -- CVPR 2022 OmniCV Workshop Challenge
Object detection is a comprehensively studied problem in autonomous driving.
ViT-BEVSeg: A Hierarchical Transformer Network for Monocular Birds-Eye-View Segmentation
In this paper, we evaluate the use of vision transformers (ViT) as a backbone architecture to generate BEV maps.
2.5D Vehicle Odometry Estimation
We show, by experimental results with a DGPS/IMU reference, that this model provides highly accurate odometry estimates, compared with existing methods.
Woodscape Fisheye Semantic Segmentation for Autonomous Driving -- CVPR 2021 OmniCV Workshop Challenge
This challenge served as a medium to investigate the challenges and new methodologies to handle the complexities with perception on fisheye images.
OdoViz: A 3D Odometry Visualization and Processing Tool
OdoViz is a reactive web-based tool for 3D visualization and processing of autonomous vehicle datasets designed to support common tasks in visual place recognition research.
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.
Computer vision in automated parking systems: Design, implementation and challenges
In this paper, we discuss the design and implementation of an automated parking system from the perspective of computer vision algorithms.
Vision-based Driver Assistance Systems: Survey, Taxonomy and Advances
Vision-based driver assistance systems is one of the rapidly growing research areas of ITS, due to various factors such as the increased level of safety requirements in automotive, computational power in embedded systems, and desire to get closer to autonomous driving.
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.
Expanding n-gram analytics in ELAN and a case study for sign synthesis
Corpus analysis is a powerful tool for signed language synthesis.
A Synergistic Approach for Recovering Occlusion-Free Textured 3D Maps of Urban Facades from Heterogeneous Cartographic Data
In this paper we present a practical approach for generating an occlusion-free textured 3D map of urban facades by the synergistic use of terrestrial images, 3D point clouds and area-based information.
