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 51–100 of 304 papers

TitleStatusHype
DATAP-SfM: Dynamic-Aware Tracking Any Point for Robust Structure from Motion in the Wild—0
USP-Gaussian: Unifying Spike-based Image Reconstruction, Pose Correction and Gaussian SplattingCode0
Activating Self-Attention for Multi-Scene Absolute Pose RegressionCode1
Robust Two-View Geometry Estimation with Implicit DifferentiationCode0
Look Gauss, No Pose: Novel View Synthesis using Gaussian Splatting without Accurate Pose InitializationCode2
Enhancing Soccer Camera Calibration Through Keypoint ExploitationCode2
MonST3R: A Simple Approach for Estimating Geometry in the Presence of MotionCode5
PuzzleBoard: A New Camera Calibration Pattern with Position EncodingCode1
GS-EVT: Cross-Modal Event Camera Tracking based on Gaussian SplattingCode1
ADen: Adaptive Density Representations for Sparse-view Camera Pose Estimation—0
Correspondence-Guided SfM-Free 3D Gaussian Splatting for NVS—0
Visual SLAM with 3D Gaussian Primitives and Depth Priors Enabling Novel View Synthesis—0
E^3NeRF: Efficient Event-Enhanced Neural Radiance Fields from Blurry Images—0
DreamCar: Leveraging Car-specific Prior for in-the-wild 3D Car ReconstructionCode2
RADA: Robust and Accurate Feature Learning with Domain Adaptation—0
Hybrid Structure-from-Motion and Camera Relocalization for Enhanced Egocentric LocalizationCode0
SCIPaD: Incorporating Spatial Clues into Unsupervised Pose-Depth Joint LearningCode1
MVSBoost: An Efficient Point Cloud-based 3D Reconstruction—0
GLACE: Global Local Accelerated Coordinate EncodingCode2
Intensity and Texture Correction of Omnidirectional Image Using Camera Images for Indirect Augmented Reality—0
Toon3D: Seeing Cartoons from New Perspectives—0
GISR: Geometric Initialization and Silhouette-based Refinement for Single-View Robot Pose and Configuration Estimation—0
LetsGo: Large-Scale Garage Modeling and Rendering via LiDAR-Assisted Gaussian Primitives—0
DepthMOT: Depth Cues Lead to a Strong Multi-Object TrackerCode1
Human Mesh Recovery from Arbitrary Multi-view ImagesCode1
WHAC: World-grounded Humans and CamerasCode3
FAR: Flexible, Accurate and Robust 6DoF Relative Camera Pose Estimation—0
Single-image camera calibration with model-free distortion correction—0
Cameras as Rays: Pose Estimation via Ray DiffusionCode4
GIM: Learning Generalizable Image Matcher From Internet VideosCode4
Learning to Produce Semi-dense Correspondences for Visual LocalizationCode2
Extreme Two-View Geometry From Object Poses with Diffusion ModelsCode1
SGS-SLAM: Semantic Gaussian Splatting For Neural Dense SLAMCode3
Multi-Person 3D Pose Estimation from Multi-View Uncalibrated Depth Cameras—0
RGBD Objects in the Wild: Scaling Real-World 3D Object Learning from RGB-D Videos—0
MobileARLoc: On-device Robust Absolute Localisation for Pervasive Markerless Mobile AR—0
SCENES: Subpixel Correspondence Estimation With Epipolar Supervision—0
FAR: Flexible Accurate and Robust 6DoF Relative Camera Pose Estimation—0
Unifying Correspondence Pose and NeRF for Generalized Pose-Free Novel View Synthesis—0
SplaTAM: Splat Track & Map 3D Gaussians for Dense RGB-D SLAM—0
iFusion: Inverting Diffusion for Pose-Free Reconstruction from Sparse ViewsCode1
Manydepth2: Motion-Aware Self-Supervised Multi-Frame Monocular Depth Estimation in Dynamic ScenesCode1
iComMa: Inverting 3D Gaussian Splatting for Camera Pose Estimation via Comparing and MatchingCode0
COLMAP-Free 3D Gaussian SplattingCode2
Unifying Correspondence, Pose and NeRF for Pose-Free Novel View Synthesis from Stereo PairsCode1
Correspondences of the Third Kind: Camera Pose Estimation from Object Reflection—0
SplaTAM: Splat, Track & Map 3D Gaussians for Dense RGB-D SLAMCode4
Pose Estimation and Tracking for ASIST—0
Robot Hand-Eye Calibration using Structure-from-Motion—0
Learning Robust Multi-Scale Representation for Neural Radiance Fields from Unposed Images—0
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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