Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Relax Image-Specific Prompt Requirement in SAM: A Single Generic Prompt for Segmenting Camouflaged Objects
Jian Hu, Jiayi Lin, Shaogang Gong, et al.
Proceedings of the AAAI Conference on Artificial Intelligence (2024) Vol. 38, Iss. 11, pp. 12511-12518
Open Access | Times Cited: 12

Showing 12 citing articles:

Language-guided reasoning segmentation for underwater images
Mingde Yao, Kimberly Tam, Menglu Wang, et al.
Information Fusion (2025), pp. 103177-103177
Closed Access
MLLM as video narrator: Mitigating modality imbalance in video moment retrieval
Weitong Cai, Jiabo Huang, Shaogang Gong, et al.
Pattern Recognition (2025), pp. 111670-111670
Closed Access
Explainability and vision foundation models: A survey
Rémi Kazmierczak, Eloïse Berthier, Goran Frehse, et al.
Information Fusion (2025), pp. 103184-103184
Closed Access
Learning from Orthogonal Space with Multimodal Large Models for Generalized Few-shot Segmentation
Xiaojie Zhou, Hang Yu, Shengjie Yang, et al.
ACM Transactions on Multimedia Computing Communications and Applications (2025)
Closed Access
Double-Branch Camouflaged Object Detection Method Based on Intra-Layer and Inter-Layer Information Integration
Hang Sun, Cong Zhang
IEEE Access (2024) Vol. 12, pp. 81057-81066
Open Access | Times Cited: 2
Chain of Visual Perception: Harnessing Multimodal Large Language Models for Zero-shot Camouflaged Object Detection
Lv Tang, Peng-Tao Jiang, Zhihui Shen, et al.
(2024), pp. 8805-8814
Closed Access | Times Cited: 1
SAMS : One-Shot Learning for the Segment Anything Model Using Similar Images
Fan Yin, Jun Li, Yifei Wei, et al.
2022 International Joint Conference on Neural Networks (IJCNN) (2024) Vol. 21, pp. 1-8
Closed Access
Reducing Training Data Using Pre-Trained Foundation Models: A Case Study on Traffic Sign Segmentation Using the Segment Anything Model
Sofia Henninger, Maximilian Kellner, Benedikt Rombach, et al.
Journal of Imaging (2024) Vol. 10, Iss. 9, pp. 220-220
Open Access
CamoTeacher: Dual-Rotation Consistency Learning for Semi-supervised Camouflaged Object Detection
Xin Lai, Zheng Yang, Jie Hu, et al.
Lecture notes in computer science (2024), pp. 438-455
Closed Access
A Survey of Camouflaged Object Detection and Beyond
Fengyang Xiao, Sujie Hu, Yuqi Shen, et al.
CAAI Artificial Intelligence Research (2024), pp. 9150044-9150044
Open Access
Utilizing grounded SAM for self-supervised frugal camouflaged human detection
Matthias Pijarowski, Alexander Wolpert, Martin Heckmann, et al.
(2024)
Open Access
Unlocking Attributes’ Contribution to Successful Camouflage: A Combined Textual and Visual Analysis Strategy
Hong Zhang, Yixuan Lyu, Qian Yu, et al.
Lecture notes in computer science (2024), pp. 315-331
Closed Access
Page 1

Scroll to top