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.
KptLLM++: Towards Generic Keypoint Comprehension with Large Language Model
FPC-Net: Revisiting SuperPoint with Descriptor-Free Keypoint Detection via Feature Pyramids and Consistency-Based Implicit Matching
Doodle Your Keypoints: Sketch-Based Few-Shot Keypoint Detection
MK-Pose: Category-Level Object Pose Estimation via Multimodal-Based Keypoint Learning
Reading a Ruler in the Wild
TimePoint: Accelerated Time Series Alignment via Self-Supervised Keypoint and Descriptor Learning
Why Not Replace? Sustaining Long-Term Visual Localization via Handcrafted-Learned Feature Collaboration on CPU
SEPT: Standard-Definition Map Enhanced Scene Perception and Topology Reasoning for Autonomous Driving
Keypoints as Dynamic Centroids for Unified Human Pose and Segmentation
Enabling Privacy-Aware AI-Based Ergonomic Analysis
RDD: Robust Feature Detector and Descriptor using Deformable Transformer
My Emotion on your face: The use of Facial Keypoint Detection to preserve Emotions in Latent Space Editing
Unsupervised Deep Learning-based Keypoint Localization Estimating Descriptor Matching Performance
Unsupervised training of keypoint-agnostic descriptors for flexible retinal image registration
Learning a General Model: Folding Clothing with Topological Dynamics
EdgePoint2: Compact Descriptors for Superior Efficiency and Accuracy
UKDM: Underwater keypoint detection and matching using underwater image enhancement techniques
Stereophotoclinometry Revisited
SuperEvent: Cross-Modal Learning of Event-based Keypoint Detection
Multiscale Feature Importance-based Bit Allocation for End-to-End Feature Coding for Machines
Keypoint Detection and Description for Raw Bayer Images
DaD: Distilled Reinforcement Learning for Diverse Keypoint Detection
REF-VLM: Triplet-Based Referring Paradigm for Unified Visual Decoding
Spatial regularisation for improved accuracy and interpretability in keypoint-based registration
Periodontal Bone Loss Analysis via Keypoint Detection With Heuristic Post-Processing
A Novel Streamline-based diffusion MRI Tractography Registration Method with Probabilistic Keypoint Detection
CNSv2: Probabilistic Correspondence Encoded Neural Image Servo
Automatic Temporal Segmentation for Post-Stroke Rehabilitation: A Keypoint Detection and Temporal Segmentation Approach for Small Datasets
Rewards-based image analysis in microscopy
2.5D U-Net with Depth Reduction for 3D CryoET Object Identification
Video-based Surgical Tool-tip and Keypoint Tracking using Multi-frame Context-driven Deep Learning Models
Transfer Learning for Keypoint Detection in Low-Resolution Thermal TUG Test Images
Keypoint Detection Empowered Near-Field User Localization and Channel Reconstruction
MIFNet: Learning Modality-Invariant Features for Generalizable Multimodal Image Matching
Refinement Module based on Parse Graph of Feature Map for Human Pose Estimation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.