4 papers · 1 filter
YOLOE: Real-Time Seeing Anything
Ao Wang, Lihao Liu, Hui Chen +3
Object detection and segmentation are widely employed in computer vision applications, yet conventional models like YOLO series, while efficient and accurate, are limited by predef…
YOLO-UniOW: Efficient Universal Open-World Object Detection
Lihao Liu, Juexiao Feng, Hui Chen +4
Traditional object detection models are constrained by the limitations of closed-set datasets, detecting only categories encountered during training. While multimodal models have e…
YOLOv10: Real-Time End-to-End Object Detection
Ao Wang, Hui Chen, Lihao Liu +4
Over the past years, YOLOs have emerged as the predominant paradigm in the field of real-time object detection owing to their effective balance between computational cost and detec…
Context Enhancement with Reconstruction as Sequence for Unified Unsupervised Anomaly Detection
Hui-Yue Yang, Hui Chen, Lihao Liu +5
Unsupervised anomaly detection (AD) aims to train robust detection models using only normal samples, while can generalize well to unseen anomalies. Recent research focuses on a uni…