SOTAVerified

Visual Localization

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

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 176–200 of 402 papers

TitleStatusHype
Ego-Motion Alignment from Face Detections for Collaborative Augmented Reality—0
Learning Scene Geometry for Visual Localization in Challenging Conditions—0
Connecting Visual Experiences using Max-flow Network with Application to Visual Localization—0
3D Gaussian Splatting aided Localization for Large and Complex Indoor-Environments—0
Efficient Privacy-Preserving Visual Localization Using 3D Ray Clouds—0
Efficient Linear Attention for Fast and Accurate Keypoint Matching—0
Combining Absolute and Semi-Generalized Relative Poses for Visual Localization—0
Coarse-To-Fine Visual Localization Using Semantic Compact Map—0
Learning Feature Matching via Matchable Keypoint-Assisted Graph Neural Network—0
Improving Nighttime Retrieval-Based Localization—0
LoGS: Visual Localization via Gaussian Splatting with Fewer Training Images—0
Long-Term Invariant Local Features via Implicit Cross-Domain Correspondences—0
Long-term Visual Localization with Mobile Sensors—0
Monocular Localization with Semantics Map for Autonomous Vehicles—0
LDP-Feat: Image Features with Local Differential Privacy—0
Dynamic Objects Segmentation for Visual Localization in Urban Environments—0
Lazy Visual Localization via Motion Averaging—0
Learning Local Features with Context Aggregation for Visual Localization—0
Efficient Large-Scale Localization by Global Instance Recognition—0
Learning models for visual 3D localization with implicit mapping—0
Localization and Control of Magnetic Suture Needles in Cluttered Surgical Site with Blood and Tissue—0
Learning Multi-View Camera Relocalization With Graph Neural Networks—0
Learning Navigation by Visual Localization and Trajectory Prediction—0
Large-scale Localization Datasets in Crowded Indoor Spaces—0
Language Guided Local Infiltration for Interactive Image Retrieval—0
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All datasetsOxford Radar RobotCar (Full-6)Aachen Day-Night v1.1 BenchmarkOxford RobotCar FullExtended CMU SeasonsRobotCar Seasons v2

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1MapNetMean Translation Error48.21—Unverified
2PointNetVLADMean Translation Error28.48—Unverified
3DCPMean Translation Error18.45—Unverified
4AD-MapNetMean Translation Error18.43—Unverified
5AtLoc+Mean Translation Error17.92—Unverified
6PosePNMean Translation Error16.32—Unverified
7VMLocMean Translation Error15.11—Unverified
8MS-TransformerMean Translation Error11.69—Unverified
9PoseMinkLocMean Translation Error11.2—Unverified
10PosePN++Mean Translation Error10.64—Unverified
#ModelMetricClaimedVerifiedStatus
1GIM-LoFTRAcc@0.25m, 2°79.1—Unverified
2LoFTRAcc@0.25m, 2°78.5—Unverified
3GIM-SuperGlueAcc@0.25m, 2°78—Unverified
4GIM-DKMAcc@0.25m, 2°77—Unverified
5SuperGlueAcc@0.25m, 2°77—Unverified
6SCFeatAcc@0.25m, 2°74.3—Unverified
7DKMAcc@0.25m, 2°70.2—Unverified
#ModelMetricClaimedVerifiedStatus
1AtLocMean Translation Error29.6—Unverified
2MapNet++Mean Translation Error29.5—Unverified
3GNNMapNetMean Translation Error17.35—Unverified
4CoordiNetMean Translation Error14.96—Unverified
5AtLoc+Mean Translation Error13.7—Unverified
6RobustLocMean Translation Error9.37—Unverified
#ModelMetricClaimedVerifiedStatus
1Patch-NetVLADAcc @ .25m, 2°0.12—Unverified
#ModelMetricClaimedVerifiedStatus
1Patch-NetVLADAcc @ .25m, 2°0.1—Unverified