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Keypoint Detection
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Keypoint Detection is essential for analyzing and interpreting images in computer vision. It involves simultaneously detecting and localizing interesting points in an image. Keypoints, also known as interest points, are spatial locations or points in the image that define what is interesting or what stands out. They are invariant to image rotation, shrinkage, translation, distortion, etc. Keypoints examples are body joints, facial landmarks, or any other salient points in objects. Keypoints have uses in problems such as pose estimation, object detection and tracking, facial analysis, and augmented reality.
<span style="color:grey; opacity: 0.6">( Image credit: PifPaf: Composite Fields for Human Pose Estimation; "Learning to surf" by fotologic, license: CC-BY-2.0 )</span>
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
ZeroKey: Point-Level Reasoning and Zero-Shot 3D Keypoint Detection from Large Language Models
Enhancing Scene Coordinate Regression with Efficient Keypoint Detection and Sequential Information
Measure Anything: Real-time, Multi-stage Vision-based Dimensional Measurement using Segment Anything
MamKPD: A Simple Mamba Baseline for Real-Time 2D Keypoint Detection
Detection, Pose Estimation and Segmentation for Multiple Bodies: Closing the Virtuous Circle
Edge Weight Prediction For Category-Agnostic Pose Estimation
OCDet: Object Center Detection via Bounding Box-Aware Heatmap Prediction on Edge Devices with NPUs
IoT-Based 3D Pose Estimation and Motion Optimization for Athletes: Application of C3D and OpenPose
KptLLM: Unveiling the Power of Large Language Model for Keypoint Comprehension
Silver medal Solution for Image Matching Challenge 2024
From Web Data to Real Fields: Low-Cost Unsupervised Domain Adaptation for Agricultural Robots
Facial Chick Sexing: An Automated Chick Sexing System From Chick Facial Image
Unsupervised Model Diagnosis
Self-Supervised Keypoint Detection with Distilled Depth Keypoint Representation
Key-Grid: Unsupervised 3D Keypoints Detection using Grid Heatmap Features
OpenKD: Opening Prompt Diversity for Zero- and Few-shot Keypoint Detection
SKT: Integrating State-Aware Keypoint Trajectories with Vision-Language Models for Robotic Garment Manipulation
GSplatLoc: Grounding Keypoint Descriptors into 3D Gaussian Splatting for Improved Visual Localization
Precision Aquaculture: An Integrated Computer Vision and IoT Approach for Optimized Tilapia Feeding
D4: Text-guided diffusion model-based domain adaptive data augmentation for vineyard shoot detection
Center Direction Network for Grasping Point Localization on Cloths
Sapiens: Foundation for Human Vision Models
Certifying Robustness of Learning-Based Keypoint Detection and Pose Estimation Methods
SHIC: Shape-Image Correspondences with no Keypoint Supervision
RADA: Robust and Accurate Feature Learning with Domain Adaptation
Multi-Grained Contrast for Data-Efficient Unsupervised Representation Learning
Scale-Free Image Keypoints Using Differentiable Persistent Homology
CapeX: Category-Agnostic Pose Estimation from Textual Point Explanation
Benchmarking Fish Dataset and Evaluation Metric in Keypoint Detection -- Towards Precise Fish Morphological Assessment in Aquaculture Breeding
A Self-Supervised Method for Body Part Segmentation and Keypoint Detection of Rat Images
SkelFormer: Markerless 3D Pose and Shape Estimation using Skeletal Transformers
Instance-Adaptive and Geometric-Aware Keypoint Learning for Category-Level 6D Object Pose Estimation
Self-supervised 3D Patient Modeling with Multi-modal Attentive Fusion
A Self-supervised Pressure Map human keypoint Detection Approch: Optimizing Generalization and Computational Efficiency Across Datasets
3D Kinematics Estimation from Video with a Biomechanical Model and Synthetic Training Data
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.