Yingda Lyu
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View article: User Invariant Preference Learning for Multi-Behavior Recommendation
User Invariant Preference Learning for Multi-Behavior Recommendation Open
In multi-behavior recommendation scenarios, analyzing users’ diverse behaviors, such as click , purchase , and rating , enables a more comprehensive understanding of their interests, facilitating personalized and accurate recommendations. …
View article: Skeleton-based Action Recognition with Non-linear Dependency Modeling and Hilbert-Schmidt Independence Criterion
Skeleton-based Action Recognition with Non-linear Dependency Modeling and Hilbert-Schmidt Independence Criterion Open
Human skeleton-based action recognition has long been an indispensable aspect of artificial intelligence. Current state-of-the-art methods tend to consider only the dependencies between connected skeletal joints, limiting their ability to …
View article: Causal-Inspired Multitask Learning for Video-Based Human Pose Estimation
Causal-Inspired Multitask Learning for Video-Based Human Pose Estimation Open
Video-based human pose estimation has long been a fundamental yet challenging problem in computer vision. Previous studies focus on spatio-temporal modeling through the enhancement of architecture design and optimization strategies. Howeve…
View article: Causal-Inspired Multitask Learning for Video-Based Human Pose Estimation
Causal-Inspired Multitask Learning for Video-Based Human Pose Estimation Open
Video-based human pose estimation has long been a fundamental yet challenging problem in computer vision. Previous studies focus on spatio-temporal modeling through the enhancement of architecture design and optimization strategies. Howeve…
View article: Reinforced Visual Interaction Fusion Radiology Report Generation
Reinforced Visual Interaction Fusion Radiology Report Generation Open
The explosion in the number of more complex types of chest X-rays and CT scans in recent years has placed a significant workload on physicians, particularly in radiology departments, to interpret and produce radiology reports. There is the…
View article: Dataset-level Color Augmentation and Multi-scale Exploration Methods for Polyp Segmentation
Dataset-level Color Augmentation and Multi-scale Exploration Methods for Polyp Segmentation Open
Automatic segmentation of polyps from colonoscopy images plays a critical role in early screening and treatment of colorectal cancer.Although deep learning methods have made significant progress, precise polyp segmentation faces two challe…
View article: CF Model: A Coarse-to-Fine Model Based on Two-Level Local Search for Image Copy-Move Forgery Detection
CF Model: A Coarse-to-Fine Model Based on Two-Level Local Search for Image Copy-Move Forgery Detection Open
Copy-move forgery is the most predominant forgery technique in the field of digital image forgery. Block-based and interest-based are currently the two mainstream categories for copy-move forgery detection methods. However, block-based alg…
View article: Copy-Move Forgery Detection Based on Keypoint Clustering and Similar Neighborhood Search Algorithm
Copy-Move Forgery Detection Based on Keypoint Clustering and Similar Neighborhood Search Algorithm Open
Copy-move is one of the most commonly used methods of tampering with digital images. Keypoint-based detection is recognized as effective in copy-move forgery detection (CMFD). This paper proposes an efficient CMFD method via clustering SIF…