Abstract: Small object detection in UAV aerial imagery presents significant challenges due to limited pixel coverage and complex backgrounds. This paper introduces DPLR-DETR (Dynamic Position Large ...

Deep learning has been successfully applied in the field of medical diagnosis, and improving the accurate classification of ...

Gesture control robotics replaces traditional buttons and joysticks with natural hand movements. This approach improves user ...

A summary of the announcements made by vendors in the days leading up to the RSAC 2026 Conference. As hundreds of vendors ...

Timely and accurate detection of foreign objects is crucial for the safe operation of transmission lines in power grid. Currently, object detection models have more and more parameters and their ...

Abstract: Object detection is a fundamental task in computer vision, involving the prediction of bounding boxes and class labels for Regions of Interest (ROI) within images. Traditionally, ...

object-detection-dataset/ ├── train/ │ ├── images/ # 800 training images │ │ ├── image_001.jpg │ │ ├── image_002.jpg ...

We’re introducing SAM 3 and SAM 3D, the newest additions to our Segment Anything Collection, which advance AI understanding of the visual world. SAM 3 enables detection and tracking of objects in ...

This project showcases a sophisticated pipeline for object detection and segmentation using a Vision-Language Model (VLM) and the Segment Anything Model 2 (SAM2). The core idea is to leverage the ...

Dyn-O: Building Structured World Models with Object-Centric Representations. Zizhao Wang, Kaixin Wang, Li Zhao, Peter Stone, and Jiang Bian. @InProceedings{dyno_neurips2025, author = {Zizhao Wang and ...