31 papers with code • 2 benchmarks • 4 datasets
These leaderboards are used to track progress in Camera Localization
Most implemented papers
DSAC - Differentiable RANSAC for Camera Localization
The most promising approach is inspired by reinforcement learning, namely to replace the deterministic hypothesis selection by a probabilistic selection for which we can derive the expected loss w. r. t.
Neural-Guided RANSAC: Learning Where to Sample Model Hypotheses
In contrast, we learn hypothesis search in a principled fashion that lets us optimize an arbitrary task loss during training, leading to large improvements on classic computer vision tasks.
Event-based Camera Pose Tracking using a Generative Event Model
Event-based vision sensors mimic the operation of biological retina and they represent a major paradigm shift from traditional cameras.
Panoramic Annular Localizer: Tackling the Variation Challenges of Outdoor Localization Using Panoramic Annular Images and Active Deep Descriptors
The panoramic annular images captured by the single camera are processed and fed into the NetVLAD network to form the active deep descriptor, and sequential matching is utilized to generate the localization result.
6D Camera Relocalization in Ambiguous Scenes via Continuous Multimodal Inference
We present a multimodal camera relocalization framework that captures ambiguities and uncertainties with continuous mixture models defined on the manifold of camera poses.
Back to the Feature: Learning Robust Camera Localization from Pixels to Pose
In this paper, we go Back to the Feature: we argue that deep networks should focus on learning robust and invariant visual features, while the geometric estimation should be left to principled algorithms.
Mapping and Localization from Planar Markers
Squared planar markers are a popular tool for fast, accurate and robust camera localization, but its use is frequently limited to a single marker, or at most, to a small set of them for which their relative pose is known beforehand.
Image Based Camera Localization: an Overview
In this paper, an overview of image based camera localization is presented.
Learning Less is More - 6D Camera Localization via 3D Surface Regression
Popular research areas like autonomous driving and augmented reality have renewed the interest in image-based camera localization.
Geometry-Aware Learning of Maps for Camera Localization
Maps are a key component in image-based camera localization and visual SLAM systems: they are used to establish geometric constraints between images, correct drift in relative pose estimation, and relocalize cameras after lost tracking.