Papers with Code 아카이브
Visual Odometry
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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Visual Odometry is an important area of information fusion in which the central aim is to estimate the pose of a robot using data collected by visual sensors.
Source: Bi-objective Optimization for Robust RGB-D Visual Odometry
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/princeton-vl/multislam_diffpose
공식 코드Multi-Session SLAM with Differentiable Wide-Baseline Pose Optimization
https://github.com/qianyuzqy/iadg
공식 코드https://github.com/remaro-network/Loss_VO_right
공식 코드Loss it right: Euclidean and Riemannian Metrics in Learning-based Visual Odometry
https://github.com/rizhaocai/metapattern_fas
공식 코드https://github.com/rlsch/depth-conversions
공식 코드Converting Depth Images and Point Clouds for Feature-based Pose Estimation
https://github.com/rpartsey/pointgoal-navigation
공식 코드https://github.com/rshaojimmy/AAAI2020-RFMetaFAS
공식 코드https://github.com/rubengooj/pl-slam
공식 코드PL-SLAM: a Stereo SLAM System through the Combination of Points and Line Segments
https://github.com/rvp-group/vbr-devkit
공식 코드https://github.com/sair-lab/iMatching
공식 코드https://github.com/sconlyshootery/FeatDepth
공식 코드Feature-metric Loss for Self-supervised Learning of Depth and Egomotion
https://github.com/searecluse/cvprw2024
공식 코드https://github.com/shuyanguni/drl_exposure_ctrl
공식 코드Efficient Camera Exposure Control for Visual Odometry via Deep Reinforcement Learning
https://github.com/sunnyhelen/jperceiver
공식 코드JPerceiver: Joint Perception Network for Depth, Pose and Layout Estimation in Driving Scenes
https://github.com/sunyiyou/safas
공식 코드Rethinking Domain Generalization for Face Anti-spoofing: Separability and Alignment
https://github.com/swami1995/v2v
공식 코드https://github.com/taylover-pei/SSDG-CVPR2020
공식 코드https://github.com/tsigalko18/transferability-testing-sdcs
공식 코드https://github.com/tub-rip/es-ptam
공식 코드https://github.com/tum-vision/devo
공식 코드https://github.com/tum-vision/tandem
공식 코드TANDEM: Tracking and Dense Mapping in Real-time using Deep Multi-view Stereo
https://github.com/tynguyen/MAVNet
공식 코드MAVNet: an Effective Semantic Segmentation Micro-Network for MAV-based Tasks
https://github.com/uestc-nnlab/lgu-slam
공식 코드https://github.com/unibwtas/yolopoint
공식 코드https://github.com/utiasSTARS/bingham-rotation-learning
공식 코드A Smooth Representation of Belief over SO(3) for Deep Rotation Learning with Uncertainty
https://github.com/utiasSTARS/cat-net
공식 코드https://github.com/utiasSTARS/dpc-net
공식 코드https://github.com/utiasSTARS/sun-bcnn-vo
공식 코드https://github.com/uzh-rpg/rampvo
공식 코드https://github.com/uzh-rpg/rl_vo
공식 코드https://github.com/uzh-rpg/rpg_davis_simulator
공식 코드https://github.com/uzh-rpg/sips2_open
공식 코드SIPs: Succinct Interest Points from Unsupervised Inlierness Probability Learning
https://github.com/valeoai/WoodScape/tree/master/omnidet
공식 코드OmniDet: Surround View Cameras based Multi-task Visual Perception Network for Autonomous Driving
https://github.com/vis-face/cdftn
공식 코드Cyclically Disentangled Feature Translation for Face Anti-spoofing
https://github.com/vis-var/lgsc-for-fas
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.