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Pose Tracking

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하위 태스크: 1
평가표: 3
보존된 평가 기록: 16

Pose Tracking is the task of estimating multi-person human poses in videos and assigning unique instance IDs for each keypoint across frames. Accurate estimation of human keypoint-trajectories is useful for human action recognition, human interaction understanding, motion capture and animation.

Source: LightTrack: A Generic Framework for Online Top-Down Human Pose Tracking

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

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

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Deep High-Resolution Representation Learning for Human Pose Estimation

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

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Simple Baselines for Human Pose Estimation and Tracking

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

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

https://github.com/li-ronghui/FineDance

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FineDance: A Fine-grained Choreography Dataset for 3D Full Body Dance Generation

https://github.com/li-ronghui/LODGE

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Lodge: A Coarse to Fine Diffusion Network for Long Dance Generation Guided by the Characteristic Dance Primitives

https://github.com/liangxuy/Inter-X

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Inter-X: Towards Versatile Human-Human Interaction Analysis

https://github.com/library87/OpenRoboExp

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Driving Animatronic Robot Facial Expression From Speech

https://github.com/lisiyao21/bailando

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Bailando: 3D Dance Generation by Actor-Critic GPT with Choreographic Memory

https://github.com/lixiny/bihand

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BiHand: Recovering Hand Mesh with Multi-stage Bisected Hourglass Networks

https://github.com/ljjtyjr/hf-slam

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High-Fidelity SLAM Using Gaussian Splatting with Rendering-Guided Densification and Regularized Optimization

https://github.com/llm-lab-org/generative-ai-for-character-animation-survey

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Generative AI for Character Animation: A Comprehensive Survey of Techniques, Applications, and Future Directions

https://github.com/lpengyang/motionclone

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MotionClone: Training-Free Motion Cloning for Controllable Video Generation

https://github.com/m-dayani/eorb_slam

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An Event-based Algorithm for Simultaneous 6-DOF Camera Pose Tracking and Mapping

https://github.com/markomih/VolumetricSMPL

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VolumetricSMPL: A Neural Volumetric Body Model for Efficient Interactions, Contacts, and Collisions

https://github.com/meaten/motionaug

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MotionAug: Augmentation with Physical Correction for Human Motion Prediction

https://github.com/mgb45/mkfbodytracker_pdaf

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Single camera pose estimation using Bayesian filtering and Kinect motion priors

https://github.com/michaelliyunhao/skeleton2humanoid

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Skeleton2Humanoid: Animating Simulated Characters for Physically-plausible Motion In-betweening

https://github.com/mingyuan-zhang/FineMoGen

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FineMoGen: Fine-Grained Spatio-Temporal Motion Generation and Editing

https://github.com/mingyuan-zhang/MotionDiffuse

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MotionDiffuse: Text-Driven Human Motion Generation with Diffusion Model

https://github.com/mingyuan-zhang/ReMoDiffuse

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ReMoDiffuse: Retrieval-Augmented Motion Diffusion Model

https://github.com/minieval/citl

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Continuous Intermediate Token Learning with Implicit Motion Manifold for Keyframe Based Motion Interpolation

https://github.com/mlgig/bodymts_2021

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Fast and Robust Video-Based Exercise Classification via Body Pose Tracking and Scalable Multivariate Time Series Classifiers

https://github.com/monkeyseedocg/momo-code

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Monkey See, Monkey Do: Harnessing Self-attention in Motion Diffusion for Zero-shot Motion Transfer

https://github.com/mrzzy2021/styledmotionsynthesis

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Unifying Human Motion Synthesis and Style Transfer with Denoising Diffusion Probabilistic Models

https://github.com/nagonch/LF_SAM_segmentation

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Segment Anything in Light Fields for Real-Time Applications via Constrained Prompting

https://github.com/nail-hnu/esvio_aa

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IMU-Aided Event-based Stereo Visual Odometry

https://github.com/nail-hnu/esvo2

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ESVO2: Direct Visual-Inertial Odometry with Stereo Event Cameras

https://github.com/nate-gillman/self-correcting-self-consuming

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Self-Correcting Self-Consuming Loops for Generative Model Training

https://github.com/nust-machine-intelligence-laboratory/videomac

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VideoMAC: Video Masked Autoencoders Meet ConvNets

https://github.com/oppo-us-research/USST

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Uncertainty-aware State Space Transformer for Egocentric 3D Hand Trajectory Forecasting

https://github.com/pabloruizponce/in2IN

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in2IN: Leveraging individual Information to Generate Human INteractions

https://github.com/patrickrperrine/comp-choreo

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KP-RNN: A Deep Learning Pipeline for Human Motion Prediction and Synthesis of Performance Art

https://github.com/pauzii/phasebetweener

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Motion In-Betweening with Phase Manifolds

https://github.com/peterfws/structure-plp-slam

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Structure PLP-SLAM: Efficient Sparse Mapping and Localization using Point, Line and Plane for Monocular, RGB-D and Stereo Cameras

https://github.com/pr-ryan/demo

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Enhancing Motion in Text-to-Video Generation with Decomposed Encoding and Conditioning

https://github.com/priormdm/priormdm

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Human Motion Diffusion as a Generative Prior

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