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
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
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
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 …