Papers with Code 아카이브

Pose Estimation

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법 전체 데이터셋

하위 태스크: 17
평가표: 31
보존된 평가 기록: 235

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/l-scofano/stag

공식 코드

Staged Contact-Aware Global Human Motion Forecasting

https://github.com/labshuhanggu/lrti-vsr

공식 코드

Small Clips, Big Gains: Learning Long-Range Refocused Temporal Information for Video Super-Resolution

https://github.com/labshuhanggu/mia-vsr

공식 코드

Video Super-Resolution Transformer with Masked Inter&Intra-Frame Attention

https://github.com/lahoud/3d-vision-transformers

공식 코드

3D Vision with Transformers: A Survey

https://github.com/laurabragagnolo/human3.6m-occluded

공식 코드

Multi-view Pose Fusion for Occlusion-Aware 3D Human Pose Estimation

https://github.com/laurenok24/nsaqa

공식 코드

Hierarchical NeuroSymbolic Approach for Comprehensive and Explainable Action Quality Assessment

https://github.com/lawy623/LSTM_Pose_Machines

공식 코드

LSTM Pose Machines

https://github.com/learninginvision/spu

공식 코드

Self-Paced Deep Regression Forests with Consideration of Ranking Fairness

https://github.com/leeiieeo/ag-pose

공식 코드

Instance-Adaptive and Geometric-Aware Keypoint Learning for Category-Level 6D Object Pose Estimation

https://github.com/leeyegy/SimDR

공식 코드

SimCC: a Simple Coordinate Classification Perspective for Human Pose Estimation

https://github.com/leeyegy/TokenPose

공식 코드

TokenPose: Learning Keypoint Tokens for Human Pose Estimation

https://github.com/lehduong/onediffusion

공식 코드

One Diffusion to Generate Them All

https://github.com/leijue222/Intra-and-Inter-Human-Relation-Network-for-MPEE

공식 코드

I^2R-Net: Intra- and Inter-Human Relation Network for Multi-Person Pose Estimation

https://github.com/leolyliu/teg-track

공식 코드

Enhancing Generalizable 6D Pose Tracking of an In-Hand Object with Tactile Sensing

https://github.com/leomingyangli/semanticslam

공식 코드

SemanticSLAM: Learning based Semantic Map Construction and Robust Camera Localization

https://github.com/leonidk/fuzzy-metaballs

공식 코드

Approximate Differentiable Rendering with Algebraic Surfaces

https://github.com/leoxiaobin/deep-high-resolution-net.pytorch

공식 코드

Deep High-Resolution Representation Learning for Human Pose Estimation

https://github.com/leoxiaobin/pose.pytorch

공식 코드

Simple Baselines for Human Pose Estimation and Tracking

https://github.com/levenberg/2D-3D-pose-tracking

공식 코드

Monocular Camera Localization in Prior LiDAR Maps with 2D-3D Line Correspondences

https://github.com/lewisjiang/contour-context

공식 코드

Contour Context: Abstract Structural Distribution for 3D LiDAR Loop Detection and Metric Pose Estimation

https://github.com/leylakhaleghi/muvihand

공식 코드

Multi-View Video-Based 3D Hand Pose Estimation

https://github.com/lhyfst/dsfnet

공식 코드

DSFNet: Dual Space Fusion Network for Occlusion-Robust 3D Dense Face Alignment

https://github.com/lihaoy-ux/dqo-map

공식 코드

DQO-MAP: Dual Quadrics Multi-Object mapping with Gaussian Splatting

https://github.com/lijenchang/Mask2Hand

공식 코드

Mask2Hand: Learning to Predict the 3D Hand Pose and Shape from Shadow

https://github.com/limaosen0/AS-GCN

공식 코드

Actional-Structural Graph Convolutional Networks for Skeleton-based Action Recognition

https://github.com/limi44/Parkinson-s-Pose-Estimation-Dataset

공식 코드

Vision-Based Assessment of Parkinsonism and Levodopa-Induced Dyskinesia with Deep Learning Pose Estimation

https://github.com/lin-jinwei/OneTo3D

공식 코드

OneTo3D: One Image to Re-editable Dynamic 3D Model and Video Generation

https://github.com/linjing7/VR-Baseline

공식 코드

Unsupervised Flow-Aligned Sequence-to-Sequence Learning for Video Restoration

https://github.com/linyicheng1/orb_slam3_localization

공식 코드

Why Not Replace? Sustaining Long-Term Visual Localization via Handcrafted-Learned Feature Collaboration on CPU

https://github.com/liruilong940607/OCHumanApi

공식 코드

Pose2Seg: Detection Free Human Instance Segmentation

https://github.com/liruilong940607/Pose2Seg

공식 코드

Pose2Seg: Detection Free Human Instance Segmentation

https://github.com/lishuhuai527/coco-unihuman

공식 코드

You Only Learn One Query: Learning Unified Human Query for Single-Stage Multi-Person Multi-Task Human-Centric Perception

https://github.com/littlewhitesea/STDAN

공식 코드

STDAN: Deformable Attention Network for Space-Time Video Super-Resolution

https://github.com/liuruijin17/clgo

공식 코드

Learning to Predict 3D Lane Shape and Camera Pose from a Single Image via Geometry Constraints

https://github.com/liuyangme/sota-3dhpe-hmr

공식 코드

Deep learning for 3D human pose estimation and mesh recovery: A survey

https://github.com/liuyuan-pal/gen6d

공식 코드

Gen6D: Generalizable Model-Free 6-DoF Object Pose Estimation from RGB Images

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.