Camera Relocalization
16 papers with code • 0 benchmarks • 2 datasets
"Camera relocalization, or image-based localization is a fundamental problem in robotics and computer vision. It refers to the process of determining camera pose from the visual scene representation and it is essential for many applications such as navigation of autonomous vehicles, structure from motion (SfM), augmented reality (AR) and simultaneous localization and mapping (SLAM)." (Source)
Benchmarks
These leaderboards are used to track progress in Camera Relocalization
Cambridge Landmarks
DeepLoc
Latest papers with no code
WSCLoc: Weakly-Supervised Sparse-View Camera Relocalization
Despite the advancements in deep learning for camera relocalization tasks, obtaining ground truth pose labels required for the training process remains a costly endeavor.
EffLoc: Lightweight Vision Transformer for Efficient 6-DOF Camera Relocalization
Camera relocalization is pivotal in computer vision, with applications in AR, drones, robotics, and autonomous driving.
Semantic Object-level Modeling for Robust Visual Camera Relocalization
Due to the improvement of CNN-based object detection algorithm, the robustness of visual relocalization is greatly enhanced especially in viewpoints where classical methods fail.
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.
Graph Attention Network for Camera Relocalization on Dynamic Scenes
We devise a graph attention network-based approach for learning a scene triangle mesh representation in order to estimate an image camera position in a dynamic environment.
OA-SLAM: Leveraging Objects for Camera Relocalization in Visual SLAM
Our fully automatic system allows on-the-fly object mapping and enhanced pose tracking recovery, which we think, can significantly benefit to the AR community.
6D Camera Relocalization in Visually Ambiguous Extreme Environments
To this end, we propose: (i) a hierarchical localization system, where we leverage temporal information and (ii) a novel environment-aware image enhancement method to boost the robustness and accuracy.
HARU: Haptic Augmented Reality-Assisted User-Centric Industrial Network Planning
To support Industry 4. 0 applications with haptics and human-machine interaction, 6G requires a new framework that is fully autonomous, visual, and interactive.
Objects Matter: Learning Object Relation Graph for Robust Camera Relocalization
Visual relocalization aims to estimate the pose of a camera from one or more images.
S3E-GNN: Sparse Spatial Scene Embedding with Graph Neural Networks for Camera Relocalization
In the GNN query module, the pose graph is transformed to form a embedding-aggregated reference graph for camera relocalization.
