Fetching the paper…
Reading the bibliography…
Camouflaged object detection is a challenging task that aims to identify objects that are highly similar to their background.
Olaf Ronneberger, Philipp Fischer, and Thomas Brox, ‘U-net: Convolutional networks for biomedical image segmentation’, in MICCAI
2015
Earlier work this paper cites.
Jascha Sohl-Dickstein, Eric Weiss, Niru Maheswaranathan, and Surya Ganguli, ‘Deep unsupervised learning using nonequilibrium thermodynamics’, in International Conference on Machine Learning
2015
Earlier work this paper cites.
Przemysław Skurowski, Hassan Abdulameer, J Błaszczyk, Tomasz Depta, Adam Kornacki, and P Kozieł, ‘Animal camouflage analysis: Chameleon database’, Unpublished manuscript
2018
Earlier work this paper cites.
Trung-Nghia Le, Tam V Nguyen, Zhongliang Nie, Minh-Triet Tran, and Akihiro Sugimoto, ‘Anabranch network for camouflaged object segmentation’, CVIU
2019
Earlier work this paper cites.
Yang Song and Stefano Ermon, ‘Generative modeling by estimating gradients of the data distribution’, NeurIPS
2019
Earlier work this paper cites.
Zhe Wu, Li Su, and Qingming Huang, ‘Cascaded partial decoder for fast and accurate salient object detection’, in CVPR
2019
Earlier work this paper cites.
Jia-Xing Zhao, Jiang-Jiang Liu, Deng-Ping Fan, Yang Cao, Jufeng Yang, and Ming-Ming Cheng, ‘Egnet: Edge guidance network for salient object detection’, in ICCV
2019
Earlier work this paper cites.
Deng-Ping Fan, Ge-Peng Ji, Guolei Sun, Ming-Ming Cheng, Jianbing Shen, and Ling Shao, ‘Camouflaged object detection’, in CVPR
2020
Earlier work this paper cites.
Deng-Ping Fan, Ge-Peng Ji, Tao Zhou, Geng Chen, Huazhu Fu, Jianbing Shen, and Ling Shao, ‘Pranet: Parallel reverse attention network for polyp segmentation’, in MICCAI
2020
Earlier work this paper cites.
Deng-Ping Fan, Tao Zhou, Ge-Peng Ji, Yi Zhou, Geng Chen, Huazhu Fu, Jianbing Shen, and Ling Shao, ‘Inf-net: Automatic covid-19 lung infection segmentation from ct images’, IEEE Transactions on Medical Imaging
2020
Earlier work this paper cites.
Jonathan Ho, Ajay Jain, and Pieter Abbeel, ‘Denoising diffusion probabilistic models’, NeurIPS
2020
Earlier work this paper cites.
Youwei Pang, Xiaoqi Zhao, Lihe Zhang, and Huchuan Lu, ‘Multi-scale interactive network for salient object detection’, in CVPR
2020
Earlier work this paper cites.
2020
Earlier work this paper cites.
Domen Tabernik, Samo Šela, Jure Skvarč, and Danijel Skočaj, ‘Segmentation-based deep-learning approach for surface-defect detection’, Journal of Intelligent Manufacturing
2020
Earlier work this paper cites.
2021
Earlier work this paper cites.
Max Daniels, Tyler Maunu, and Paul Hand, ‘Score-based generative neural networks for large-scale optimal transport’, NeurIPS
2021
Earlier work this paper cites.
Prafulla Dhariwal and Alexander Nichol, ‘Diffusion models beat gans on image synthesis’, NeurIPS
2021
Earlier work this paper cites.
Deng-Ping Fan, Ge-Peng Ji, Ming-Ming Cheng, and Ling Shao, ‘Concealed object detection’, IEEE TPAMI
2021
Earlier work this paper cites.
Karthika Suresh Kumar and Aamer Abdul Rahman, ‘Early detection of locust swarms using deep learning’, in Advances in machine learning and computational intelligence
2021
Earlier work this paper cites.
Aixuan Li, Jing Zhang, Yunqiu Lv, Bowen Liu, Tong Zhang, and Yuchao Dai, ‘Uncertainty-aware joint salient object and camouflaged object detection’, in CVPR
2021
Earlier work this paper cites.
Lin Li, Jingyi Liu, Fei Yu, Xunkun Wang, and Tian-Zhu Xiang, ‘Mvdi25k: A large-scale dataset of microscopic vaginal discharge images’, BenchCouncil Transactions on Benchmarks, Standards and Evaluations
2021
Earlier work this paper cites.
Yunqiu Lv, Jing Zhang, Yuchao Dai, Aixuan Li, Bowen Liu, Nick Barnes, and Deng-Ping Fan, ‘Simultaneously localize, segment and rank the camouflaged objects’, in CVPR
2021
Earlier work this paper cites.
Haiyang Mei, Ge-Peng Ji, Ziqi Wei, Xin Yang, Xiaopeng Wei, and Deng-Ping Fan, ‘Camouflaged object segmentation with distraction mining’, in CVPR
2021
Cited alongside, same era.
2021
Cited alongside, same era.
Alexander Quinn Nichol and Prafulla Dhariwal, ‘Improved denoising diffusion probabilistic models’, in ICML
2021
Cited alongside, same era.
Aditya Prakash, Kashyap Chitta, and Andreas Geiger, ‘Multi-modal fusion transformer for end-to-end autonomous driving’, in CVPR
2021
Cited alongside, same era.
Yujia Sun, Geng Chen, Tao Zhou, Yi Zhang, and Nian Liu, ‘Context-aware cross-level fusion network for camouflaged object detection’, IJCAI
2021
Wenhai Wang, Enze Xie, Xiang Li, Deng-Ping Fan, Kaitao Song, Ding Liang, Tong Lu, Ping Luo, and Ling Shao, ‘Pvtv2: Improved baselines with pyramid vision transformer’, Computational Visual Media
2022
Later among the works it cites.
2022
Later among the works it cites.
Cong Zhang, Kang Wang, Hongbo Bi, Ziqi Liu, and Lina Yang, ‘Camouflaged object detection via neighbor connection and hierarchical information transfer’, CVIU
2022
Later among the works it cites.
Miao Zhang, Shuang Xu, Yongri Piao, Dongxiang Shi, Shusen Lin, and Huchuan Lu, ‘Preynet: Preying on camouflaged objects’, in ACM MM
2022
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Qiang Zhai, Xin Li, Fan Yang, Chenglizhao Chen, Hong Cheng, and Deng-Ping Fan, ‘Mutual graph learning for camouflaged object detection’, in CVPR
2021
Cited alongside, same era.
Jinchao Zhu, Xiaoyu Zhang, Shuo Zhang, and Junnan Liu, ‘Inferring camouflaged objects by texture-aware interactive guidance network’, in AAAI
2021
Cited alongside, same era.
Dmitry Baranchuk, Andrey Voynov, Ivan Rubachev, Valentin Khrulkov, and Artem Babenko, ‘Label-efficient semantic segmentation with diffusion models’, in ICLR
2022
Cited alongside, same era.
Emmanuel Asiedu Brempong, Simon Kornblith, Ting Chen, Niki Parmar, Matthias Minderer, and Mohammad Norouzi, ‘Denoising pretraining for semantic segmentation’, in CVPR
2022
Cited alongside, same era.
Xuelian Cheng, Huan Xiong, Deng-Ping Fan, Yiran Zhong, Mehrtash Harandi, Tom Drummond, and Zongyuan Ge, ‘Implicit motion handling for video camouflaged object detection’, in CVPR
2022
Cited alongside, same era.
Hyungjin Chung, Byeongsu Sim, and Jong Chul Ye, ‘Come-closer-diffuse-faster: Accelerating conditional diffusion models for inverse problems through stochastic contraction’, in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition
2022
Cited alongside, same era.
2022
Cited alongside, same era.
2022
Later among the works it cites.
Hongwei Zhu, Peng Li, Haoran Xie, Xuefeng Yan, Dong Liang, Dapeng Chen, Mingqiang Wei, and Jing Qin, ‘I can find you! boundary-guided separated attention network for camouflaged object detection’, in AAAI
2022
Later among the works it cites.
Mingchen Zhuge, Xiankai Lu, Yiyou Guo, Zhihua Cai, and Shuhan Chen, ‘Cubenet: X-shape connection for camouflaged object detection’, Pattern Recognition
2022
Later among the works it cites.
2023
Closest in time.
Florinel-Alin Croitoru, Vlad Hondru, Radu Tudor Ionescu, and Mubarak Shah, ‘Diffusion models in vision: A survey’, IEEE TPAMI
2023
Closest in time.
Bo Dong, Jialun Pei, Rongrong Gao, Tian-Zhu Xiang, Shuo Wang, and Huan Xiong, ‘A unified query-based paradigm for camouflaged instance segmentation’, in ACM MM
2023
Closest in time.
2023
Closest in time.
Ruozhen He, Qihua Dong, Jiaying Lin, and Rynson WH Lau, ‘Weakly-supervised camouflaged object detection with scribble annotations’, AAAI
2023
Closest in time.
Xiaobin Hu, Shuo Wang, Xuebin Qin, Hang Dai, Wenqi Ren, Donghao Luo, Ying Tai, and Ling Shao, ‘High-resolution iterative feedback network for camouflaged object detection’, AAAI
2023
Closest in time.
Zhou Huang, Hang Dai, Tian-Zhu Xiang, Shuo Wang, Huai-Xin Chen, Jie Qin, and Huan Xiong, ‘Feature shrinkage pyramid for camouflaged object detection with transformers’, CVPR
2023
Closest in time.
Ge-Peng Ji, Deng-Ping Fan, Yu-Cheng Chou, Dengxin Dai, Alexander Liniger, and Luc Van Gool, ‘Deep gradient learning for efficient camouflaged object detection’, Machine Intelligence Research
2023
Closest in time.
2023
Closest in time.
2023
Closest in time.
Aimon Rahman, Jeya Maria Jose Valanarasu, Ilker Hacihaliloglu, and Vishal M Patel, ‘Ambiguous medical image segmentation using diffusion models’, in CVPR
2023
Closest in time.
Junde Wu, Huihui Fang, Yu Zhang, Yehui Yang, and Yanwu Xu, ‘Medsegdiff: Medical image segmentation with diffusion probabilistic model’, MIDL
2023
Closest in time.
2023
Closest in time.
Weijia Wu, Yuzhong Zhao, Mike Zheng Shou, Hong Zhou, and Chunhua Shen, ‘Diffumask: Synthesizing images with pixel-level annotations for semantic segmentation using diffusion models’, ICCV
2023
Closest in time.
Jiarui Xu, Sifei Liu, Arash Vahdat, Wonmin Byeon, Xiaolong Wang, and Shalini De Mello, ‘Open-vocabulary panoptic segmentation with text-to-image diffusion models’, CVPR
2023
Closest in time.