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Benchmarking neural radiance fields for autonomous robots: An overview
Abstract Neural Radiance Field (NeRF) has emerged as a powerful paradigm for scene
representation, offering high-fidelity renderings and reconstructions from a set of sparse and …
representation, offering high-fidelity renderings and reconstructions from a set of sparse and …
Scene coordinate reconstruction: Posing of image collections via incremental learning of a relocalizer
E Brachmann, J Wynn, S Chen, T Cavallari… - … on Computer Vision, 2024 - Springer
We address the task of estimating camera parameters from a set of images depicting a
scene. Popular feature-based structure-from-motion (SfM) tools solve this task by …
scene. Popular feature-based structure-from-motion (SfM) tools solve this task by …
Pope: 6-dof promptable pose estimation of any object in any scene with one reference
Despite the significant progress in six degrees-of-freedom (6DoF) object pose estimation
existing methods have limited applicability in real-world scenarios involving embodied …
existing methods have limited applicability in real-world scenarios involving embodied …
Crossfire: Camera relocalization on self-supervised features from an implicit representation
A Moreau, N Piasco, M Bennehar… - Proceedings of the …, 2023 - openaccess.thecvf.com
Beyond novel view synthesis, Neural Radiance Fields are useful for applications that
interact with the real world. In this paper, we use them as an implicit map of a given scene …
interact with the real world. In this paper, we use them as an implicit map of a given scene …
Scanerf: Scalable bundle-adjusting neural radiance fields for large-scale scene rendering
High-quality large-scale scene rendering requires a scalable representation and accurate
camera poses. This research combines tile-based hybrid neural fields with parallel …
camera poses. This research combines tile-based hybrid neural fields with parallel …
Ai-generated images as data source: The dawn of synthetic era
The advancement of visual intelligence is intrinsically tethered to the availability of large-
scale data. In parallel, generative Artificial Intelligence (AI) has unlocked the potential to …
scale data. In parallel, generative Artificial Intelligence (AI) has unlocked the potential to …
Learning to estimate 6dof pose from limited data: A few-shot, generalizable approach using rgb images
The accurate estimation of six degrees-of-freedom (6DoF) object poses is essential for many
applications in robotics and augmented reality. However, existing methods for 6DoF pose …
applications in robotics and augmented reality. However, existing methods for 6DoF pose …
6dgs: 6d pose estimation from a single image and a 3d gaussian splatting model
B Matteo, T Tsesmelis, S James, F Poiesi… - European Conference on …, 2024 - Springer
We propose 6DGS to estimate the camera pose of a target RGB image given a 3D Gaussian
Splatting (3DGS) model representing the scene. 6DGS avoids the iterative process typical of …
Splatting (3DGS) model representing the scene. 6DGS avoids the iterative process typical of …
Nerf in robotics: A survey
Meticulous 3D environment representations have been a longstanding goal in computer
vision and robotics fields. The recent emergence of neural implicit representations has …
vision and robotics fields. The recent emergence of neural implicit representations has …
Nvist: In the wild new view synthesis from a single image with transformers
We propose NViST a transformer-based model for efficient and generalizable novel-view
synthesis from a single image for real-world scenes. In contrast to many methods that are …
synthesis from a single image for real-world scenes. In contrast to many methods that are …