9 citations · 15 across the 5 of their papers we have counts for
5 papers
Real-Time Object Detection Meets DINOv3
Shihua Huang, Yongjie Hou, Longfei Liu +2
Driven by the simple and effective Dense O2O, DEIM demonstrates faster convergence and enhanced performance. In this work, we extend it with DINOv3 features, resulting in DEIMv2. D…
SimROD: A Simple Baseline for Raw Object Detection with Global and Local Enhancements
Haiyang Xie, Xi Shen, Shihua Huang +2
Most visual models are designed for sRGB images, yet RAW data offers significant advantages for object detection by preserving sensor information before ISP processing. This enable…
DEIM: DETR with Improved Matching for Fast Convergence
Shihua Huang, Zhichao Lu, Xiaodong Cun +3
We introduce DEIM, an innovative and efficient training framework designed to accelerate convergence in real-time object detection with Transformer-based architectures (DETR). To m…
From COCO to COCO-FP: A Deep Dive into Background False Positives for COCO Detectors
Longfei Liu, Wen Guo, Shihua Huang +2
Reducing false positives is essential for enhancing object detector performance, as reflected in the mean Average Precision (mAP) metric. Although object detectors have achieved no…
Technique Report of CVPR 2024 PBDL Challenges
Ying Fu, Yu Li, Shaodi You +96
The intersection of physics-based vision and deep learning presents an exciting frontier for advancing computer vision technologies. By leveraging the principles of physics to info…