https://github.com/garrickbrazil/M3D-RPN
공식 코드M3D-RPN: Monocular 3D Region Proposal Network for Object Detection
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/garvita-tiwari/sizer
공식 코드SIZER: A Dataset and Model for Parsing 3D Clothing and Learning Size Sensitive 3D Clothing
https://github.com/garyzhao/SemGCN
공식 코드Semantic Graph Convolutional Networks for 3D Human Pose Regression
https://github.com/gbarbarani/MorseDet
공식 코드Scale-Free Image Keypoints Using Differentiable Persistent Homology
https://github.com/geekfeiw/WiSPPN
공식 코드https://github.com/geekfeiw/wifiperson
공식 코드https://github.com/gengzigang/pct
공식 코드https://github.com/genintel/novum
공식 코드NOVUM: Neural Object Volumes for Robust Object Classification
https://github.com/genintel/uns-obj-pose3d
공식 코드Unsupervised Learning of Category-Level 3D Pose from Object-Centric Videos
https://github.com/georgeretsi/mushroom-pose
공식 코드https://github.com/giddyyupp/coco-minitrain
공식 코드HoughNet: Integrating near and long-range evidence for visual detection
https://github.com/gkouros/contrastive-pose-retrieval
공식 코드Category-Level Pose Retrieval with Contrastive Features Learnt with Occlusion Augmentation
https://github.com/gnina/gnina
공식 코드https://github.com/gnns4hri/3d_multi_pose_estimator
공식 코드https://github.com/gohyojun15/SplatFlow
공식 코드SplatFlow: Multi-View Rectified Flow Model for 3D Gaussian Splatting Synthesis
https://github.com/goldbricklemon/uplift-upsample-3dhpe
공식 코드Uplift and Upsample: Efficient 3D Human Pose Estimation with Uplifting Transformers
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/DMSR
공식 코드RGB-based Category-level Object Pose Estimation via Decoupled Metric Scale Recovery
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/google-research/cad-estate
공식 코드https://github.com/google-research/google-research
공식 코드View-Invariant, Occlusion-Robust Probabilistic Embedding for Human Pose
https://github.com/google-research/google-research/tree/master/comisr
공식 코드https://github.com/google-research/google-research/tree/master/implicit_pdf
공식 코드Implicit-PDF: Non-Parametric Representation of Probability Distributions on the Rotation Manifold
https://github.com/google-research/google-research/tree/master/keypose
공식 코드KeyPose: Multi-View 3D Labeling and Keypoint Estimation for Transparent Objects
https://github.com/google-research/google-research/tree/master/metapose
공식 코드MetaPose: Fast 3D Pose from Multiple Views without 3D Supervision
https://github.com/google-research/google-research/tree/master/special_orthogonalization
공식 코드https://github.com/google-research/mint
공식 코드AI Choreographer: Music Conditioned 3D Dance Generation with AIST++
https://github.com/google-research/nerf-from-image
공식 코드Shape, Pose, and Appearance from a Single Image via Bootstrapped Radiance Field Inversion
https://github.com/google-research/pix2seq
공식 코드https://github.com/google/mediapipe
공식 코드https://github.com/gorilla-lab-scut/bico-net
공식 코드BiCo-Net: Regress Globally, Match Locally for Robust 6D Pose Estimation
https://github.com/gorilla-lab-scut/dcl-net
공식 코드DCL-Net: Deep Correspondence Learning Network for 6D Pose Estimation
https://github.com/gorilla-lab-scut/mast
공식 코드Manifold-Aware Self-Training for Unsupervised Domain Adaptation on Regressing 6D Object Pose
https://github.com/gorilla-lab-scut/ss-conv
공식 코드https://github.com/graformer/graformer
공식 코드GraFormer: Graph Convolution Transformer for 3D Pose Estimation
https://github.com/great-whu/sf-loc
공식 코드SF-Loc: A Visual Mapping and Geo-Localization System based on Sparse Visual Structure Frames
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.