[HTML][HTML] A survey of state-of-the-art on visual SLAM
This paper is an overview to Visual Simultaneous Localization and Mapping (V-SLAM). We
discuss the basic definitions in the SLAM and vision system fields and provide a review of …
discuss the basic definitions in the SLAM and vision system fields and provide a review of …
Deep learning sensor fusion for autonomous vehicle perception and localization: A review
Autonomous vehicles (AV) are expected to improve, reshape, and revolutionize the future of
ground transportation. It is anticipated that ordinary vehicles will one day be replaced with …
ground transportation. It is anticipated that ordinary vehicles will one day be replaced with …
Sparf: Neural radiance fields from sparse and noisy poses
P Truong, MJ Rakotosaona… - Proceedings of the …, 2023 - openaccess.thecvf.com
Abstract Neural Radiance Field (NeRF) has recently emerged as a powerful representation
to synthesize photorealistic novel views. While showing impressive performance, it relies on …
to synthesize photorealistic novel views. While showing impressive performance, it relies on …
Understanding the limitations of cnn-based absolute camera pose regression
Visual localization is the task of accurate camera pose estimation in a known scene. It is a
key problem in computer vision and robotics, with applications including self-driving cars …
key problem in computer vision and robotics, with applications including self-driving cars …
Relpose: Predicting probabilistic relative rotation for single objects in the wild
We describe a data-driven method for inferring the camera viewpoints given multiple images
of an arbitrary object. This task is a core component of classic geometric pipelines such as …
of an arbitrary object. This task is a core component of classic geometric pipelines such as …
Geometric loss functions for camera pose regression with deep learning
Deep learning has shown to be effective for robust and real-time monocular image
relocalisation. In particular, PoseNet is a deep convolutional neural network which learns to …
relocalisation. In particular, PoseNet is a deep convolutional neural network which learns to …
Visual SLAM and structure from motion in dynamic environments: A survey
In the last few decades, Structure from Motion (SfM) and visual Simultaneous Localization
and Mapping (visual SLAM) techniques have gained significant interest from both the …
and Mapping (visual SLAM) techniques have gained significant interest from both the …
Viewformer: Nerf-free neural rendering from few images using transformers
Novel view synthesis is a long-standing problem. In this work, we consider a variant of the
problem where we are given only a few context views sparsely covering a scene or an …
problem where we are given only a few context views sparsely covering a scene or an …
Deep auxiliary learning for visual localization and odometry
Localization is an indispensable component of a robot's autonomy stack that enables it to
determine where it is in the environment, essentially making it a precursor for any action …
determine where it is in the environment, essentially making it a precursor for any action …
Vlocnet++: Deep multitask learning for semantic visual localization and odometry
Semantic understanding and localization are fundamental enablers of robot autonomy that
have been tackled as disjoint problems for the most part. While deep learning has enabled …
have been tackled as disjoint problems for the most part. While deep learning has enabled …