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- 3D-Aided Deep Pose-Invariant Face Recognition83
A 3D-Aided Deep Pose-Invariant Face Recognition Model (3D-PIM), which automatically recovers realistic frontal faces from arbitrary poses through a 3D face model in a novel way, and demonstrates superiority of the proposed model over state-of-the-arts.
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- RECAP: Towards Precise Radiology Report Generation via Dynamic Disease Progression Reasoning39
RECAP is proposed, which generates precise and accurate radiology reports via dynamic disease progression reasoning via dynamic progression reasoning, and combines the historical records, spatiotemporal information, and radiographs for report generation.
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- Keyword-Aware Relative Spatio-Temporal Graph Networks for Video Question Answering19
A Keyword-aware Relative Spatio-Temporal graph network for VideoQA that employs an attention mechanism to assign high weights to keywords during question encoding and integrates the relative relation modeling to better capture the spatio-temporal dynamics among object nodes.
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- Improved Particle Filter Algorithm for Multi-Target Detection and Tracking17
Experimental result shows that the proposed particle filter algorithm for multi-target detection and tracking can effectively improve the detection probability, and it has a lower root mean square error (RMSE) and a stronger adaptability to multi-target situation.
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- MCPA: multi-scale cross perceptron attention network for 2D medical image segmentation9
This work proposes a 2D medical image segmentation model called multi-scale cross perceptron attention network (MCPA), and introduces a progressive dual-branch structure (PDBS) to address the semantic segmentation of the image involving finer tissue structures.
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- KubFBS: A fine‐grained and balance‐aware scheduling system for deep learning tasks based on kubernetes8
A fine‐grained and balance‐aware scheduling model (FBSM) which considers the resource consumption characteristic of the DL task and is proposed to construct a scheduling system called KubFBS, which accelerates the execution of DL tasks while improving the load balancing capability of the cluster.
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- SkatingVerse: A large‐scale benchmark for comprehensive evaluation on human action understanding7
SkatingVerse significantly helps the training and evaluation of HAU methods, the performance of existing HAU methods has much room to improve, and SkatingVerse helps to reduce such gaps, and unifying relevant tasks in HAU through a uniform dataset can facilitate more practical applications.
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- PEVA-Net: Prompt-enhanced view aggregation network for zero/few-shot multi-view 3D shape recognition6
Publication data from OpenAlex, with missing venues and authors filled in from Crossref; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-12. One-sentence summaries under some papers are written by Semantic Scholar’s model. Citation counts may be lower than on Google Scholar, which indexes more sources.
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