Visual Localization

90 papers with code • 2 benchmarks • 16 datasets

Visual Localization is the problem of estimating the camera pose of a given image relative to a visual representation of a known scene.

Source: Fine-Grained Segmentation Networks: Self-Supervised Segmentation for Improved Long-Term Visual Localization


Use these libraries to find Visual Localization models and implementations

Most implemented papers

DSAC - Differentiable RANSAC for Camera Localization

cvlab-dresden/DSAC CVPR 2017

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.

BARF: Bundle-Adjusting Neural Radiance Fields

chenhsuanlin/bundle-adjusting-NeRF 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 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

dadung/Visual-Localization-Filtering 20 Nov 2018

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

ethz-asl/hfnet CVPR 2019

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 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.

AdaLAM: Revisiting Handcrafted Outlier Detection

cavalli1234/AdaLAM 7 Jun 2020

Local feature matching is a critical component of many computer vision pipelines, including among others Structure-from-Motion, SLAM, and Visual Localization.

Patch-NetVLAD: Multi-Scale Fusion of Locally-Global Descriptors for Place Recognition

QVPR/Patch-NetVLAD CVPR 2021

Visual Place Recognition is a challenging task for robotics and autonomous systems, which must deal with the twin problems of appearance and viewpoint change in an always changing world.

LoFTR: Detector-Free Local Feature Matching with Transformers

zju3dv/LoFTR CVPR 2021

We present a novel method for local image feature matching.

CrossLoc: Scalable Aerial Localization Assisted by Multimodal Synthetic Data

topo-epfl/crossloc CVPR 2022

We present a visual localization system that learns to estimate camera poses in the real world with the help of synthetic data.