Papers with Code 아카이브
Visual Localization
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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Visual Localization is the problem of estimating the camera pose of a given image relative to a visual representation of a known scene.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/82magnolia/panoramic-localization
공식 코드https://github.com/82magnolia/piccolo
공식 코드https://github.com/AAnoosheh/ToDayGAN
공식 코드Night-to-Day Image Translation for Retrieval-based Localization
https://github.com/ActiveVisionLab/LaLaLoc
공식 코드LaLaLoc: Latent Layout Localisation in Dynamic, Unvisited Environments
https://github.com/AdaCompNUS/pfnet
공식 코드Particle Filter Networks with Application to Visual Localization
https://github.com/BingCS/AtLoc
공식 코드https://github.com/BingCS/P2-Net
공식 코드P2-Net: Joint Description and Detection of Local Features for Pixel and Point Matching
https://github.com/CapsuleEndoscope/VirtualCapsuleEndoscopy
공식 코드https://github.com/DLR-RM/ExReNet
공식 코드Learning to Localize in New Environments from Synthetic Training Data
https://github.com/EasonChen99/EVLoc
공식 코드EVLoc: Event-based Visual Localization in LiDAR Maps via Event-Depth Registration
https://github.com/GeWu-Lab/Generalizable-Audio-Visual-Segmentation
공식 코드Prompting Segmentation with Sound Is Generalizable Audio-Visual Source Localizer
https://github.com/GrumpyZhou/patch2pix
공식 코드https://github.com/HanjiangHu/DASGIL
공식 코드DASGIL: Domain Adaptation for Semantic and Geometric-aware Image-based Localization
https://github.com/HanjiangHu/DIFL-FCL
공식 코드Retrieval-based Localization Based on Domain-invariant Feature Learning under Changing Environments
https://github.com/HanjiangHu/DISAM
공식 코드https://github.com/HuajianUP/360Loc
공식 코드360Loc: A Dataset and Benchmark for Omnidirectional Visual Localization with Cross-device Queries
https://github.com/HyHuang1995/gmmloc
공식 코드https://github.com/IIT-PAVIS/Flatlandia
공식 코드3DoF Localization from a Single Image and an Object Map: the Flatlandia Problem and Dataset
https://github.com/JethroJames/CREST
공식 코드CREST: Cross-modal Resonance through Evidential Deep Learning for Enhanced Zero-Shot Learning
https://github.com/LCAD-UFES/WNN-CNN-GL
공식 코드https://github.com/MIT-SPARK/Kimera
공식 코드Kimera: from SLAM to Spatial Perception with 3D Dynamic Scene Graphs
https://github.com/Mingpan/generative_map
공식 코드https://github.com/NVlabs/geomapnet
공식 코드https://github.com/QVPR/Patch-NetVLAD
공식 코드Patch-NetVLAD: Multi-Scale Fusion of Locally-Global Descriptors for Place Recognition
https://github.com/SeasonDepth/SeasonDepth
공식 코드https://github.com/TOPO-EPFL/TOPO-DataGen
공식 코드CrossLoc: Scalable Aerial Localization Assisted by Multimodal Synthetic Data
https://github.com/TUMFTM/orbslam-map-saving-extension
공식 코드Persistent Map Saving for Visual Localization for Autonomous Vehicles: An ORB-SLAM Extension
https://github.com/VictorZoo/LoD-Loc
공식 코드LoD-Loc: Aerial Visual Localization using LoD 3D Map with Neural Wireframe Alignment
https://github.com/WangYueFt/dcp
공식 코드Deep Closest Point: Learning Representations for Point Cloud Registration
https://github.com/XRIM-Lab/GS-CPR
공식 코드GSLoc: Efficient Camera Pose Refinement via 3D Gaussian Splatting
https://github.com/YapengTian/AV-Robustness-CVPR21
공식 코드Can audio-visual integration strengthen robustness under multimodal attacks?
https://github.com/Yux1angJi/GTA-UAV
공식 코드https://github.com/aaltovision/cl_hscnet
공식 코드https://github.com/acuooooo/resmatch
공식 코드ResMatch: Residual Attention Learning for Local Feature Matching
https://github.com/aervisloc/vpair
공식 코드VPAIR -- Aerial Visual Place Recognition and Localization in Large-scale Outdoor Environments
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.