2 citations · 9 across the 12 of their papers we have counts for
12 papers
Gated-BEPO: Confidence-Gated Bellman Credit Assignment for Large Language Model Agents
Hongxi Yan, Ziyue Huang, Shichao Fan +1
Training large language model agents in long-horizon environments requires assigning credit from sparse terminal outcomes to individual actions. Existing critic-free methods propag…
Beyond Open Vocabulary: Multimodal Prompting for Object Detection in Remote Sensing Images
Shuai Yang, Ziyue Huang, Jiaxin Chen +2
Open-vocabulary object detection in remote sensing commonly relies on text-only prompting to specify target categories, implicitly assuming that inference-time category queries can…
Vision-Language Model for Object Detection and Segmentation: A Review and Evaluation
Yongchao Feng, Yajie Liu, Shuai Yang +13
Vision-Language Model (VLM) have gained widespread adoption in Open-Vocabulary (OV) object detection and segmentation tasks. Despite they have shown promise on OV-related tasks, th…
A Survey on Remote Sensing Foundation Models: From Vision to Multimodality
Ziyue Huang, Hongxi Yan, Qiqi Zhan +7
The rapid advancement of remote sensing foundation models, particularly vision and multimodal models, has significantly enhanced the capabilities of intelligent geospatial data int…
OpenRSD: Towards Open-prompts for Object Detection in Remote Sensing Images
Ziyue Huang, Yongchao Feng, Shuai Yang +3
Remote sensing object detection has made significant progress, but most studies still focus on closed-set detection, limiting generalization across diverse datasets. Open-vocabular…
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…
MutDet: Mutually Optimizing Pre-training for Remote Sensing Object Detection
Ziyue Huang, Yongchao Feng, Qingjie Liu +1
Detection pre-training methods for the DETR series detector have been extensively studied in natural scenes, e.g., DETReg. However, the detection pre-training remains unexplored in…
YOLC: You Only Look Clusters for Tiny Object Detection in Aerial Images
Chenguang Liu, Guangshuai Gao, Ziyue Huang +3
Detecting objects from aerial images poses significant challenges due to the following factors: 1) Aerial images typically have very large sizes, generally with millions or even hu…
Generic Knowledge Boosted Pre-training For Remote Sensing Images
Ziyue Huang, Mingming Zhang, Yuan Gong +2
Deep learning models are essential for scene classification, change detection, land cover segmentation, and other remote sensing image understanding tasks. Most backbones of existi…
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…
Incremental Object Detection with CLIP
Ziyue Huang, Yupeng He, Qingjie Liu +1
In contrast to the incremental classification task, the incremental detection task is characterized by the presence of data ambiguity, as an image may have differently labeled boun…
Context-Enhanced Detector For Building Detection From Remote Sensing Images
Ziyue Huang, Mingming Zhang, Qingjie Liu +3
The field of building detection from remote sensing images has made significant progress, but faces challenges in achieving high-accuracy detection due to the diversity in building…