2 citations · 4 across the 9 of their papers we have counts for
9 papers
Prompt-Calibrated SAM 3 for Open-Vocabulary Remote Sensing Semantic Segmentation
Yanghui Song, Nanqing Liu, Haonan Yin +3
Open-vocabulary semantic segmentation (OVSS) in remote sensing images aims to segment categories beyond a fixed label space. Recent SAM 3-based methods provide a promising training…
DroneFINE: Domain-Aware Parameter-Efficient Fine-Tuning of Vision-Language Detectors for Drone Images
Ke Wu, Yanan Zhang, Yingjie Gao +5
Object detection for Unmanned Aerial Vehicles (UAVs) working in open and dynamic environments is a highly challenging task. While Vision-Language Models (VLMs) have offered a power…
Towards Unbiased Source-Free Object Detection via Vision Foundation Models
Zhi Cai, Yingjie Gao, Yanan Zhang +2
Source-Free Object Detection (SFOD) has garnered much attention in recent years by eliminating the need of source-domain data in cross-domain tasks, but existing SFOD methods suffe…
Test-Time Adaptive Object Detection with Foundation Model
Yingjie Gao, Yanan Zhang, Zhi Cai +1
In recent years, test-time adaptive object detection has attracted increasing attention due to its unique advantages in online domain adaptation, which aligns more closely with rea…
PS-TTL: Prototype-based Soft-labels and Test-Time Learning for Few-shot Object Detection
Yingjie Gao, Yanan Zhang, Ziyue Huang +2
In recent years, Few-Shot Object Detection (FSOD) has gained widespread attention and made significant progress due to its ability to build models with a good generalization power…
Crowd-SAM: SAM as a Smart Annotator for Object Detection in Crowded Scenes
Zhi Cai, Yingjie Gao, Yaoyan Zheng +2
In computer vision, object detection is an important task that finds its application in many scenarios. However, obtaining extensive labels can be challenging, especially in crowde…
Semantic Enhanced Few-shot Object Detection
Zheng Wang, Yingjie Gao, Qingjie Liu +1
Few-shot object detection~(FSOD), which aims to detect novel objects with limited annotated instances, has made significant progress in recent years. However, existing methods stil…
DSD-DA: Distillation-based Source Debiasing for Domain Adaptive Object Detection
Yongchao Feng, Shiwei Li, Yingjie Gao +4
Though feature-alignment based Domain Adaptive Object Detection (DAOD) methods have achieved remarkable progress, they ignore the source bias issue, i.e., the detector tends to acq…
Semi-Supervised Object Detection with Uncurated Unlabeled Data for Remote Sensing Images
Nanqing Liu, Xun Xu, Yingjie Gao +1
Annotating remote sensing images (RSIs) presents a notable challenge due to its labor-intensive nature. Semi-supervised object detection (SSOD) methods tackle this issue by generat…