https://github.com/facebookresearch/fast3r
공식 코드Fast3R: Towards 3D Reconstruction of 1000+ Images in One Forward Pass
Papers with Code 아카이브
Camera Pose Estimation
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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.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/facebookresearch/silk
공식 코드https://github.com/fengyi233/SCIPaD
공식 코드SCIPaD: Incorporating Spatial Clues into Unsupervised Pose-Depth Joint Learning
https://github.com/gohyojun15/SplatFlow
공식 코드SplatFlow: Multi-View Rectified Flow Model for 3D Gaussian Splatting Synthesis
https://github.com/goldoak/APnP
공식 코드AEP$n$P: A Less-constrained EP$n$P Solver for Pose Estimation with Anisotropic Scaling
https://github.com/goldoak/aepnp
공식 코드AEP$n$P: A Less-constrained EP$n$P Solver for Pose Estimation with Anisotropic Scaling
https://github.com/haleqiu/airdos
공식 코드https://github.com/hamburgerlady/fast_planar_camera_pose
공식 코드https://github.com/hannahhaensen/dynamon
공식 코드DynaMoN: Motion-Aware Fast and Robust Camera Localization for Dynamic Neural Radiance Fields
https://github.com/henry123-boy/Level-S2FM_official
공식 코드Level-S$^2$fM: Structure from Motion on Neural Level Set of Implicit Surfaces
https://github.com/henry123-boy/SpaTrackerV2
공식 코드https://github.com/hlzz/DeepMatchVO
공식 코드Beyond Photometric Loss for Self-Supervised Ego-Motion Estimation
https://github.com/hongsukchoi/hsfm_release
공식 코드https://github.com/icetttb/nopesac
공식 코드NOPE-SAC: Neural One-Plane RANSAC for Sparse-View Planar 3D Reconstruction
https://github.com/inception3d/easi3r
공식 코드Easi3R: Estimating Disentangled Motion from DUSt3R Without Training
https://github.com/irmvlab/3dunmonoflow
공식 코드Unsupervised Learning of 3D Scene Flow from Monocular Camera
https://github.com/jacklangerman/dance
공식 코드https://github.com/jackwoo0831/depthmot
공식 코드https://github.com/jkulhanek/viewformer
공식 코드ViewFormer: NeRF-free Neural Rendering from Few Images Using Transformers
https://github.com/jonathanventura/p1ac
공식 코드P1AC: Revisiting Absolute Pose From a Single Affine Correspondence
https://github.com/k032131/EPOSIT
공식 코드EPOSIT: An Absolute Pose Estimation Method for Pinhole and Fish-Eye Cameras
https://github.com/kunalchelani/Line2Point
공식 코드How Privacy-Preserving are Line Clouds? Recovering Scene Details from 3D Lines
https://github.com/lehduong/onediffusion
공식 코드https://github.com/lulufa390/Pan-tilt-zoom-SLAM
공식 코드https://github.com/ma-mehralian/ekfpnp_matlab_toolbox
공식 코드EKFPnP: Extended Kalman Filter for Camera Pose Estimation in a Sequence of Images
https://github.com/magicleap/SuperGluePretrainedNetwork
공식 코드SuperGlue: Learning Feature Matching with Graph Neural Networks
https://github.com/mgb45/mkfbodytracker_pdaf
공식 코드Single camera pose estimation using Bayesian filtering and Kinect motion priors
https://github.com/naver/croco
공식 코드CroCo: Self-Supervised Pre-training for 3D Vision Tasks by Cross-View Completion
https://github.com/naver/kapture-localization
공식 코드https://github.com/nianticlabs/monodepth2
공식 코드https://github.com/nianticlabs/scoring-without-correspondences
공식 코드https://github.com/openxrlab/xrfeitoria
공식 코드https://github.com/parskatt/dkm
공식 코드DKM: Dense Kernelized Feature Matching for Geometry Estimation
https://github.com/parskatt/roma
공식 코드https://github.com/puzzlepaint/camera_calibration
공식 코드Why Having 10,000 Parameters in Your Camera Model is Better Than Twelve
https://github.com/qhfang/accurateacl
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.