1 citations · 2 across the 5 of their papers we have counts for
5 papers
Online Pseudo-Label Unified Object Detection for Multiple Datasets Training
XiaoJun Tang, Jingru Wang, Zeyu Shangguan +2
The Unified Object Detection (UOD) task aims to achieve object detection of all merged categories through training on multiple datasets, and is of great significance in comprehensi…
Cross-Domain Few-Shot Object Detection via Enhanced Open-Set Object Detector
Yuqian Fu, Yu Wang, Yixuan Pan +7
This paper studies the challenging cross-domain few-shot object detection (CD-FSOD), aiming to develop an accurate object detector for novel domains with minimal labeled examples.…
Decoupled DETR For Few-shot Object Detection
Zeyu Shangguan, Lian Huai, Tong Liu +1
Few-shot object detection (FSOD), an efficient method for addressing the severe data-hungry problem, has been extensively discussed. Current works have significantly advanced the p…
Few-shot Object Detection with Refined Contrastive Learning
Zeyu Shangguan, Lian Huai, Tong Liu +1
Due to the scarcity of sampling data in reality, few-shot object detection (FSOD) has drawn more and more attention because of its ability to quickly train new detection concepts w…
Distinctive Self-Similar Object Detection
Zeyu Shangguan, Bocheng Hu, Guohua Dai +3
Deep learning-based object detection has demonstrated a significant presence in the practical applications of artificial intelligence. However, objects such as fire and smoke, pose…