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Pose Estimation
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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>
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Dy3DGS-SLAM: Monocular 3D Gaussian Splatting SLAM for Dynamic Environments
LGM-Pose: A Lightweight Global Modeling Network for Real-time Human Pose Estimation
SupeRANSAC: One RANSAC to Rule Them All
DualX-VSR: Dual Axial Spatial$\times$Temporal Transformer for Real-World Video Super-Resolution without Motion Compensation
CzechLynx: A Dataset for Individual Identification and Pose Estimation of the Eurasian Lynx
Rectified Point Flow: Generic Point Cloud Pose Estimation
On-the-fly Reconstruction for Large-Scale Novel View Synthesis from Unposed Images
Voyager: Long-Range and World-Consistent Video Diffusion for Explorable 3D Scene Generation
cuVSLAM: CUDA accelerated visual odometry and mapping
GeneA-SLAM2: Dynamic SLAM with AutoEncoder-Preprocessed Genetic Keypoints Resampling and Depth Variance-Guided Dynamic Region Removal
Learning Pyramid-structured Long-range Dependencies for 3D Human Pose Estimation
A Survey of Deep Learning Video Super-Resolution
Omnidirectional Video Super-Resolution using Deep Learning
PCIE_Pose Solution for EgoExo4D Pose and Proficiency Estimation Challenge
Category-Level 6D Object Pose Estimation in Agricultural Settings Using a Lattice-Deformation Framework and Diffusion-Augmented Synthetic Data
6D Pose Estimation on Point Cloud Data through Prior Knowledge Integration: A Case Study in Autonomous Disassembly
AdaHuman: Animatable Detailed 3D Human Generation with Compositional Multiview Diffusion
TimePoint: Accelerated Time Series Alignment via Self-Supervised Keypoint and Descriptor Learning
Event-based Egocentric Human Pose Estimation in Dynamic Environment
MultiFormer: A Multi-Person Pose Estimation System Based on CSI and Attention Mechanism
4DTAM: Non-Rigid Tracking and Mapping via Dynamic Surface Gaussians
Automatic Scene Generation: State-of-the-Art Techniques, Models, Datasets, Challenges, and Future Prospects
ReassembleNet: Learnable Keypoints and Diffusion for 2D Fresco Reconstruction
UltraVSR: Achieving Ultra-Realistic Video Super-Resolution with Efficient One-Step Diffusion Space
EventEgoHands: Event-based Egocentric 3D Hand Mesh Reconstruction
Why Not Replace? Sustaining Long-Term Visual Localization via Handcrafted-Learned Feature Collaboration on CPU
Direct3D-S2: Gigascale 3D Generation Made Easy with Spatial Sparse Attention
PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation
Towards Dynamic 3D Reconstruction of Hand-Instrument Interaction in Ophthalmic Surgery
Pose Splatter: A 3D Gaussian Splatting Model for Quantifying Animal Pose and Appearance
GMatch: Geometry-Constrained Feature Matching for RGB-D Object Pose Estimation
EasyInsert: A Data-Efficient and Generalizable Insertion Policy
DOVE: Efficient One-Step Diffusion Model for Real-World Video Super-Resolution
Towards Texture- And Shape-Independent 3D Keypoint Estimation in Birds
Template-Guided 3D Molecular Pose Generation via Flow Matching and Differentiable Optimization
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.