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- MotionLab: Unified Human Motion Generation and Editing via the Motion-Condition-Motion Paradigm39
A novel paradigm is introduced: Motion-Condition-Motion, which enables the unified formulation of diverse tasks with three concepts: source motion, condition, and target motion, and a unified framework, MotionLab, which incorporates rectified flows to learn the mapping from source motion to target motion, guided by the specified conditions.
- Advances in Aircraft Skin Defect Detection Using Computer Vision: A Survey and Comparison of YOLOv9 and RT-DETR Performance24
The fundamental contribution of this paper is to underscore the potential of computer vision for aircraft skin defect detection while emphasizing that further research is still required to address existing limitations.
- Visual Prompting for One-shot Controllable Video Editing without Inversion12
Inspired by consistency models that can perform multi-step consistency sampling to generate a sequence of content-consistent images, this work proposes a content consistency sampling (CCS) to ensure content consistency between the generated edited frames and the source frames.
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- Re3Syn: A Dependency-Based Data Synthesis Framework for Long-Context Post-training4
A novel framework called Re trieval, Dependency Re cognition, and Re order for data syn thesis is proposed, which leverages semantic similarity to retrieve relevant documents and form several batches which enhances the model’s long-context capabilities.
- Leveraging Text-to-Image Diffusion Models for Unsupervised Visual Object Tracking3
The method Diff-Tracking, which learns a prompt that represents the tracking target and activates its corresponding region in the cross-attention map for each frame, which enables object tracking with the diffusion model, achieves strong performance compared to existing unsupervised trackers.
- Drone-Based Maritime Anomaly Detection with YOLO and Motion/Appearance Fusion1
This study proposes a hybrid anomaly detection and tracking pipeline that integrates YOLOv12, as the primary object detector, with two auxiliary modules: (i) motion assistance for tracking moving anomalies and (ii) stillness (appearance) assistance for tracking slow-moving or stationary anomalies.
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- Influence of Performance Metrics Emphasis in Hyperparameter Tuning for Aircraft Skin Defect Detection: An Early Inspection of Weighted Average Objectives–
This paper considers the utilization of YOLOv12 and the Bayesian Optimization approach for the defect detection model and hyperparameter optimizer, respectively and highlights the possible performance degradation of the model after a hyperparameter tuning procedure when the weight factor distribution of the performance metrics is not carefully considered.
- Computer Vision-Based Airport Turnaround Monitoring Using YOLOv11, Multi-Object Tracking, and Motion-Based Passenger and Baggage Activity Detection–
The results demonstrate that the proposed modified YOLO-based pipeline can transform ordinary airport video footage into structured operational timelines, supporting more transparent, data-driven, and automated monitoring of airport turnaround processes.
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Publication data from OpenAlex; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-11. 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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