Visual Localization
151 papers with code • 5 benchmarks • 19 datasets
Visual Localization is the problem of estimating the camera pose of a given image relative to a visual representation of a known scene.
Benchmarks
These leaderboards are used to track progress in Visual Localization
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Libraries
Use these libraries to find Visual Localization models and implementationsDatasets
NCLT
Cambridge Landmarks
Aachen Day-Night
InLoc
KAIST Urban
DeepLoc
Long-term visual localization
PhotoSynth
Most implemented papers
PointNetVLAD: Deep Point Cloud Based Retrieval for Large-Scale Place Recognition
mikacuy/pointnetvlad
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CVPR 2018
This is largely due to the difficulty in extracting local feature descriptors from a point cloud that can subsequently be encoded into a global descriptor for the retrieval task.
LoFTR: Detector-Free Local Feature Matching with Transformers
We present a novel method for local image feature matching.
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.
Deep Closest Point: Learning Representations for Point Cloud Registration
To address local optima and other difficulties in the ICP pipeline, we propose a learning-based method, titled Deep Closest Point (DCP), inspired by recent techniques in computer vision and natural language processing.
BARF: Bundle-Adjusting Neural Radiance Fields
chenhsuanlin/bundle-adjusting-NeRF
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ICCV 2021
In this paper, we propose Bundle-Adjusting Neural Radiance Fields (BARF) for training NeRF from imperfect (or even unknown) camera poses -- the joint problem of learning neural 3D representations and registering camera frames.
Neighbourhood Consensus Networks
ignacio-rocco/ncnet
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NeurIPS 2018
Second, we demonstrate that the model can be trained effectively from weak supervision in the form of matching and non-matching image pairs without the need for costly manual annotation of point to point correspondences.
Visual Localization Under Appearance Change: Filtering Approaches
Our approaches rely on local features with an encoding technique to represent an image as a single vector.
From Coarse to Fine: Robust Hierarchical Localization at Large Scale
In this paper we propose HF-Net, a hierarchical localization approach based on a monolithic CNN that simultaneously predicts local features and global descriptors for accurate 6-DoF localization.
Neural-Guided RANSAC: Learning Where to Sample Model Hypotheses
vislearn/ngransac
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ICCV 2019
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.
University-1652: A Multi-view Multi-source Benchmark for Drone-based Geo-localization
layumi/University1652-Baseline
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To our knowledge, University-1652 is the first drone-based geo-localization dataset and enables two new tasks, i. e., drone-view target localization and drone navigation.
