Papers with Code 아카이브
Pose Estimation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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Pose Estimation is a computer vision task where the goal is to detect the position and orientation of a person or an object. Usually, this is done by predicting the location of specific keypoints like hands, head, elbows, etc. in case of Human Pose Estimation.
A common benchmark for this task is MPII Human Pose
<span style="color:grey; opacity: 0.6">( Image credit: Real-time 2D Multi-Person Pose Estimation on CPU: Lightweight OpenPose )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/drsleep/nas-segm-pytorch
공식 코드Fast Neural Architecture Search of Compact Semantic Segmentation Models via Auxiliary Cells
https://github.com/dtc111111/multi-modal-uav
공식 코드https://github.com/dubenma/d-inlocpp
공식 코드https://github.com/dubiouscactus/meta-learning-hope
공식 코드https://github.com/dulucas/simlpe
공식 코드https://github.com/duncanzauss/keypoint_communities
공식 코드https://github.com/dvl-tum/center-group
공식 코드The Center of Attention: Center-Keypoint Grouping via Attention for Multi-Person Pose Estimation
https://github.com/dwawayu/pensieve
공식 코드Recollection from Pensieve: Novel View Synthesis via Learning from Uncalibrated Videos
https://github.com/dx118/dynaip
공식 코드https://github.com/dxbdxx/bpfnet
공식 코드BPFNet: A Unified Framework for Bimodal Palmprint Alignment and Fusion
https://github.com/easonyesheng/sgam
공식 코드https://github.com/eddyhkchiu/pose_forecast_wacv
공식 코드https://github.com/edi-meta-learning/meta-omnium
공식 코드Meta Omnium: A Benchmark for General-Purpose Learning-to-Learn
https://github.com/edm-research/cad2render
공식 코드https://github.com/edodema/BestPractices2Body
공식 코드https://github.com/edybk/hand-pose-estimation-for-surgical-training
공식 코드Using Hand Pose Estimation To Automate Open Surgery Training Feedback
https://github.com/edz-o/3dnbf
공식 코드3D-Aware Neural Body Fitting for Occlusion Robust 3D Human Pose Estimation
https://github.com/egulsoylu/image-ais-fusion
공식 코드Image and AIS Data Fusion Technique for Maritime Computer Vision Applications
https://github.com/eivan/one-ac-pose
공식 코드Relative Pose from Deep Learned Depth and a Single Affine Correspondence
https://github.com/ekramalam/rthfd
공식 코드Real-Time Human Fall Detection using a Lightweight Pose Estimation Technique
https://github.com/elego9/6dp-data-bias
공식 코드Uncovering the Background-Induced bias in RGB based 6-DoF Object Pose Estimation
https://github.com/eliabntt/GRADE-RR
공식 코드https://github.com/ensv/RPNet
공식 코드RPNet: an End-to-End Network for Relative Camera Pose Estimation
https://github.com/ephemeral182/empirical-study-of-gpt-4o-image-gen
공식 코드https://github.com/equinoxxxxx/spn
공식 코드Sparse Prototype Network for Explainable Pedestrian Behavior Prediction
https://github.com/eric-yyjau/pytorch-deepFEPE
공식 코드Deep Keypoint-Based Camera Pose Estimation with Geometric Constraints
https://github.com/ericcjoyce/consensus-driven-uncertainty
공식 코드Consensus-Driven Uncertainty for Robotic Grasping based on RGB Perception
https://github.com/esrschao/edgeregnet
공식 코드EdgeRegNet: Edge Feature-based Multimodal Registration Network between Images and LiDAR Point Clouds
https://github.com/esw0116/DynaVSR
공식 코드https://github.com/eth-ait/emdb
공식 코드EMDB: The Electromagnetic Database of Global 3D Human Pose and Shape in the Wild
https://github.com/eth-ait/tempclr
공식 코드TempCLR: Reconstructing Hands via Time-Coherent Contrastive Learning
https://github.com/eth-siplab/avatarposer
공식 코드AvatarPoser: Articulated Full-Body Pose Tracking from Sparse Motion Sensing
https://github.com/eth-siplab/ultrainertialposer
공식 코드https://github.com/ethanygao/training-free_generalizable_relative_pose
공식 코드Towards Human-Level 3D Relative Pose Estimation: Generalizable, Training-Free, with Single Reference
https://github.com/ethnhe/FFB6D
공식 코드FFB6D: A Full Flow Bidirectional Fusion Network for 6D Pose Estimation
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