SOTAVerified

Camera Pose Estimation

Camera pose estimation is a crucial task in computer vision and robotics that involves determining the position and orientation (pose) of a camera relative to a given reference frame. This task is essential for various applications, such as augmented reality, 3D reconstruction, SLAM, and autonomous navigation.

Papers

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Showing 26–50 of 304 papers

TitleStatusHype
PoseDiffusion: Solving Pose Estimation via Diffusion-aided Bundle AdjustmentCode2
SiLK -- Simple Learned KeypointsCode2
CroCo: Self-Supervised Pre-training for 3D Vision Tasks by Cross-View CompletionCode2
MeshLoc: Mesh-Based Visual LocalizationCode2
ParticleSfM: Exploiting Dense Point Trajectories for Localizing Moving Cameras in the WildCode2
PVO: Panoptic Visual OdometryCode2
Investigating the Role of Image Retrieval for Visual Localization -- An exhaustive benchmarkCode2
ViewFormer: NeRF-free Neural Rendering from Few Images Using TransformersCode2
DKM: Dense Kernelized Feature Matching for Geometry EstimationCode2
Princeton365: A Diverse Dataset with Accurate Camera PoseCode1
EVLoc: Event-based Visual Localization in LiDAR Maps via Event-Depth RegistrationCode1
RePoseD: Efficient Relative Pose Estimation With Known Depth InformationCode1
Learning to Filter Outlier Edges in Global SfMCode1
Enhancing Scene Coordinate Regression with Efficient Keypoint Detection and Sequential InformationCode1
Activating Self-Attention for Multi-Scene Absolute Pose RegressionCode1
PuzzleBoard: A New Camera Calibration Pattern with Position EncodingCode1
GS-EVT: Cross-Modal Event Camera Tracking based on Gaussian SplattingCode1
SCIPaD: Incorporating Spatial Clues into Unsupervised Pose-Depth Joint LearningCode1
DepthMOT: Depth Cues Lead to a Strong Multi-Object TrackerCode1
Human Mesh Recovery from Arbitrary Multi-view ImagesCode1
Extreme Two-View Geometry From Object Poses with Diffusion ModelsCode1
iFusion: Inverting Diffusion for Pose-Free Reconstruction from Sparse ViewsCode1
Manydepth2: Motion-Aware Self-Supervised Multi-Frame Monocular Depth Estimation in Dynamic ScenesCode1
Unifying Correspondence, Pose and NeRF for Pose-Free Novel View Synthesis from Stereo PairsCode1
USB-NeRF: Unrolling Shutter Bundle Adjusted Neural Radiance FieldsCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Monodepth2Average Translational Error et[%]43.21—Unverified
2SfMLearnerAverage Translational Error et[%]29.78—Unverified
3GeoNetAverage Translational Error et[%]26.31—Unverified
4SC-DepthAverage Translational Error et[%]12.2—Unverified
5DeepMatchVOAverage Translational Error et[%]11.05—Unverified
6SCIPaDAverage Translational Error et[%]8.63—Unverified
7Manydepth2Average Translational Error et[%]7.15—Unverified