https://github.com/razayunus/ManhattanSLAM
공식 코드ManhattanSLAM: Robust Planar Tracking and Mapping Leveraging Mixture of Manhattan Frames
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/rfabbri/minus
공식 코드Trifocal Relative Pose from Lines at Points and its Efficient Solution
https://github.com/sair-lab/SeqACE
공식 코드Enhancing Scene Coordinate Regression with Efficient Keypoint Detection and Sequential Information
https://github.com/schmiddo/noposegs
공식 코드https://github.com/scy639/extreme-two-view-geometry-from-object-poses-with-diffusion-models
공식 코드Extreme Two-View Geometry From Object Poses with Diffusion Models
https://github.com/shichaoy/cube_slam
공식 코드https://github.com/shiyujiao/boosting3dofaccuracy
공식 코드https://github.com/shuhongll/sgs-slam
공식 코드https://github.com/sjingjia/planerectr
공식 코드PlaneRecTR++: Unified Query Learning for Joint 3D Planar Reconstruction and Pose Estimation
https://github.com/spla-tam/splatam
공식 코드SplaTAM: Splat, Track & Map 3D Gaussians for Dense RGB-D SLAM
https://github.com/theNded/SGP
공식 코드https://github.com/thusiyuan/cooperative_scene_parsing
공식 코드Cooperative Holistic Scene Understanding: Unifying 3D Object, Layout, and Camera Pose Estimation
https://github.com/tinghuiz/SfMLearner
공식 코드https://github.com/torrvision/spaint
공식 코드Real-Time RGB-D Camera Pose Estimation in Novel Scenes using a Relocalisation Cascade
https://github.com/truongkhang/deviloc
공식 코드Learning to Produce Semi-dense Correspondences for Visual Localization
https://github.com/tsattler/meshloc_release
공식 코드https://github.com/tsattler/understanding_apr
공식 코드Understanding the Limitations of CNN-based Absolute Camera Pose Regression
https://github.com/tudelft-iv/slicematch
공식 코드SliceMatch: Geometry-guided Aggregation for Cross-View Pose Estimation
https://github.com/vcg-uvic/acne
공식 코드ACNe: Attentive Context Normalization for Robust Permutation-Equivariant Learning
https://github.com/vladpyatov/ihls
공식 코드Robust Two-View Geometry Estimation with Implicit Differentiation
https://github.com/wayne-mai/egoloc_v1
공식 코드Hybrid Structure-from-Motion and Camera Relocalization for Enhanced Egocentric Localization
https://github.com/xiaobenli00/u-hmr
공식 코드https://github.com/xiaobiaodu/DreamCar
공식 코드DreamCar: Leveraging Car-specific Prior for in-the-wild 3D Car Reconstruction
https://github.com/xuelunshen/gim
공식 코드GIM: Learning Generalizable Image Matcher From Internet Videos
https://github.com/yaqding/pose_monodepth
공식 코드RePoseD: Efficient Relative Pose Estimation With Known Depth Information
https://github.com/yzcjtr/GeoNet
공식 코드GeoNet: Unsupervised Learning of Dense Depth, Optical Flow and Camera Pose
https://github.com/zhangyuhong01/HumanMM-code
공식 코드HumanMM: Global Human Motion Recovery from Multi-shot Videos
https://github.com/zhenpeiyang/fvor
공식 코드FvOR: Robust Joint Shape and Pose Optimization for Few-view Object Reconstruction
https://github.com/zhenpeiyang/hm3d-abo
공식 코드HM3D-ABO: A Photo-realistic Dataset for Object-centric Multi-view 3D Reconstruction
https://github.com/zinsmatt/3D-Aware-Ellipses-for-Visual-Localization
공식 코드3D-Aware Ellipse Prediction for Object-Based Camera Pose Estimation
https://github.com/zju3dv/LoFTR
공식 코드LoFTR: Detector-Free Local Feature Matching with Transformers
https://github.com/zju3dv/PVO
공식 코드https://github.com/zshn25/pc4consistentdepth
공식 코드Pose Constraints for Consistent Self-supervised Monocular Depth and Ego-motion
https://gitlab.com/confidence_painting/cpaint
공식 코드Soft Expectation and Deep Maximization for Image Feature Detection
https://github.com/2023-MindSpore-1/ms-code-211/tree/main/dgcnet_res101
https://github.com/2023-MindSpore-1/ms-code-214/tree/main/fishnet99
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.