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Landmark Tracking
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논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Integrating Persian Lip Reading in Surena-V Humanoid Robot for Human-Robot Interaction
Testing MediaPipe Holistic for Linguistic Analysis of Nonmanual Markers in Sign Languages
PIPsUS: Self-Supervised Dense Point Tracking in Ultrasound
The Heat is On: Thermal Facial Landmark Tracking
1DFormer: a Transformer Architecture Learning 1D Landmark Representations for Facial Landmark Tracking
LSDM: Long-Short Diffeomorphic Motion for Weakly-Supervised Ultrasound Landmark Tracking
A Classification Model Utilizing Facial Landmark Tracking to Determine Sentence Types for American Sign Language Recognition
WarpPINN: Cine-MR image registration with physics-informed neural networks
Generalizable Deepfake Detection with Phase-Based Motion Analysis
Autonomous Asteroid Characterization Through Nanosatellite Swarming
Landmark Tracking in Liver US images Using Cascade Convolutional Neural Networks with Long Short-Term Memory
A Neuromorphic Vision-Based Measurement for Robust Relative Localization in Future Space Exploration Missions
A Human-Centered Machine-Learning Approach for Muscle-Tendon Junction Tracking in Ultrasound Images
Reasoning Structural Relation for Occlusion-Robust Facial Landmark Localization
Breaking Shortcut: Exploring Fully Convolutional Cycle-Consistency for Video Correspondence Learning
DeepTag: An Unsupervised Deep Learning Method for Motion Tracking on Cardiac Tagging Magnetic Resonance Images
Unified Multi-Modal Landmark Tracking for Tightly Coupled Lidar-Visual-Inertial Odometry
Automatic Tracking of the Muscle Tendon Junction in Healthy and Impaired Subjects using Deep Learning
Attentive One-Dimensional Heatmap Regression for Facial Landmark Detection and Tracking
Siamese Networks with Location Prior for Landmark Tracking in Liver Ultrasound Sequences
CyLKs: Unsupervised Cycle Lucas-Kanade Network for Landmark Tracking
A Functional Regression approach to Facial Landmark Tracking
Cascaded Continuous Regression for Real-time Incremental Face Tracking
Geometric Feature-Based Facial Expression Recognition in Image Sequences Using Multi-Class AdaBoost and Support Vector Machines
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.