Zotta, L.,
Matteoli, S.,
Diani, M.,
Corsini, G.,
AFRODiTE: A FluoRescence Lidar Simulator for Underwater Object
DeTEction Applications,
GeoRS(53), No. 6, June 2015, pp. 3022-3041.
IEEE DOI
1503
oceanographic regions
BibRef
Cejka, J.[Jan],
Bruno, F.[Fabio],
Skarlatos, D.[Dimitrios],
Liarokapis, F.[Fotis],
Detecting Square Markers in Underwater Environments,
RS(11), No. 4, 2019, pp. xx-yy.
DOI Link
1903
BibRef
Kannan, S.[Srividhya],
Intelligent object recognition in underwater images using
evolutionary-based Gaussian mixture model and shape matching,
SIViP(14), No. 5, July 2020, pp. 877-885.
Springer DOI
2006
BibRef
Szymak, P.[Piotr],
Piskur, P.[Pawel],
Naus, K.[Krzysztof],
The Effectiveness of Using a Pretrained Deep Learning Neural Networks
for Object Classification in Underwater Video,
RS(12), No. 18, 2020, pp. xx-yy.
DOI Link
2009
BibRef
Liu, R.,
Fan, X.,
Zhu, M.,
Hou, M.,
Luo, Z.,
Real-World Underwater Enhancement: Challenges, Benchmarks, and
Solutions Under Natural Light,
CirSysVideo(30), No. 12, December 2020, pp. 4861-4875.
IEEE DOI
2012
Image color analysis, Image enhancement, Task analysis, Histograms,
Benchmark testing, Imaging, Degradation,
object detection
BibRef
Chen, L.[Long],
Jiang, Z.[Zheheng],
Tong, L.[Lei],
Liu, Z.H.[Zhi-Hua],
Zhao, A.[Aite],
Zhang, Q.[Qianni],
Dong, J.Y.[Jun-Yu],
Zhou, H.Y.[Hui-Yu],
Perceptual Underwater Image Enhancement With Deep Learning and
Physical Priors,
CirSysVideo(31), No. 8, August 2021, pp. 3078-3092.
IEEE DOI
2108
Task analysis, Image enhancement, Image color analysis, Absorption,
Image synthesis, Deep learning, Object detection,
perceptual loss
BibRef
Zhang, M.H.[Ming-Hua],
Xu, S.[Shubo],
Song, W.[Wei],
He, Q.[Qi],
Wei, Q.[Quanmiao],
Lightweight Underwater Object Detection Based on YOLO v4 and
Multi-Scale Attentional Feature Fusion,
RS(13), No. 22, 2021, pp. xx-yy.
DOI Link
2112
BibRef
Liu, R.S.[Ri-Sheng],
Jiang, Z.Y.[Zhi-Ying],
Yang, S.Z.[Shu-Zhou],
Fan, X.[Xin],
Twin Adversarial Contrastive Learning for Underwater Image
Enhancement and Beyond,
IP(31), 2022, pp. 4922-4936.
IEEE DOI
2208
Task analysis, Image enhancement, Detectors, Image restoration,
Object detection, Image color analysis, Visualization,
generative adversarial learning
BibRef
Chen, L.[Long],
Zhou, F.X.[Fei-Xiang],
Wang, S.K.[Sheng-Ke],
Dong, J.Y.[Jun-Yu],
Li, N.[Ning],
Ma, H.P.[Hai-Ping],
Wang, X.[Xin],
Zhou, H.Y.[Hui-Yu],
SWIPENET: Object detection in noisy underwater scenes,
PR(132), 2022, pp. 108926.
Elsevier DOI
2209
Underwater object detection, Curriculum Multi-Class Adaboost,
Sample-weighted detection loss, Noisy data
BibRef
Jia, J.Q.[Jia-Qi],
Fu, M.[Min],
Liu, X.F.[Xue-Feng],
Zheng, B.[Bing],
Underwater Object Detection Based on Improved EfficientDet,
RS(14), No. 18, 2022, pp. xx-yy.
DOI Link
2209
BibRef
Fu, C.P.[Chen-Ping],
Fan, X.[Xin],
Xiao, J.[Jiewen],
Yuan, W.Q.[Wan-Qi],
Liu, R.S.[Ri-Sheng],
Luo, Z.X.[Zhong-Xuan],
Learning Heavily-Degraded Prior for Underwater Object Detection,
CirSysVideo(33), No. 11, November 2023, pp. 6887-6896.
IEEE DOI Code:
WWW Link.
2311
BibRef
Yuan, J.J.[Jiao-Jiao],
Hu, Y.L.[Yong-Li],
Sun, Y.F.[Yan-Feng],
Yin, B.C.[Bao-Cai],
A multi-scale feature representation and interaction network for
underwater object detection,
IET-CV(17), No. 3, 2023, pp. 265-281.
DOI Link
2305
convolutional neural nets, object detection
BibRef
Hua, X.[Xia],
Cui, X.P.[Xiao-Peng],
Xu, X.H.[Xing-Hua],
Qiu, S.H.[Shao-Hua],
Liang, Y.J.[Ying-Jie],
Bao, X.Q.[Xian-Qiang],
Li, Z.[Zhong],
Underwater object detection algorithm based on feature enhancement
and progressive dynamic aggregation strategy,
PR(139), 2023, pp. 109511.
Elsevier DOI
2304
Underwater image, Dynamic feature fusion,
Small object detection, Rapid spatial pyramid pooling, Feature enhancement
BibRef
Chen, G.Q.[Gang-Qi],
Mao, Z.Y.[Zhao-Yong],
Wang, K.[Kai],
Shen, J.[Junge],
HTDet: A Hybrid Transformer-Based Approach for Underwater Small
Object Detection,
RS(15), No. 4, 2023, pp. xx-yy.
DOI Link
2303
BibRef
Qin, K.S.[Ken Sinkou],
Liu, D.[Di],
Wang, F.[Fei],
Zhou, J.C.[Jing-Chun],
Yang, J.X.[Jia-Xuan],
Zhang, W.S.[Wei-Shi],
Improved YOLOv7 model for underwater sonar image object detection,
JVCIR(100), 2024, pp. 104124.
Elsevier DOI
2405
Underwater object detection, Sonar image,
Criss-Cross Attention, Model pruning, YOLOv7 model
BibRef
Wei, D.B.[De-Bin],
Xie, H.J.[Hong-Ji],
Zhang, Z.X.[Zeng-Xi],
Yan, T.T.[Tian-Tian],
Learning a Holistic-Specific color transformer with Couple
Contrastive constraints for underwater image enhancement and beyond,
JVCIR(98), 2024, pp. 104059.
Elsevier DOI
2402
Underwater image enhancement, Underwater object detection, Contrastive learning
BibRef
Dai, L.H.[Lin-Hui],
Liu, H.[Hong],
Song, P.[Pinhao],
Liu, M.Y.[Meng-Yuan],
A gated cross-domain collaborative network for underwater object
detection,
PR(149), 2024, pp. 110222.
Elsevier DOI
2403
Underwater object detection, Underwater image enhancement, Cross-domain
BibRef
Liu, Z.Y.[Zhuo-Yan],
Wang, B.[Bo],
Li, Y.[Ye],
He, J.X.[Jia-Xian],
Li, Y.F.[Yun-Feng],
UnitModule: A lightweight joint image enhancement module for
underwater object detection,
PR(151), 2024, pp. 110435.
Elsevier DOI Code:
WWW Link.
2404
Underwater object detection, Image enhancement,
Unsupervised learning, Joint training
BibRef
Wu, J.J.[Jun-Jun],
Chen, J.P.[Jin-Peng],
Lu, Q.H.[Qing-Hua],
Li, J.X.[Jia-Xi],
Qin, N.[Ningwei],
Chen, K.X.[Kai-Xuan],
Liu, X.L.[Xi-Lin],
U-ATSS: A lightweight and accurate one-stage underwater object
detection network,
SP:IC(126), 2024, pp. 117137.
Elsevier DOI
2406
Marine environment, Underwater robot, Object detection,
One-stage, Lightweight network
BibRef
Vlachos, A.[Apostolos],
Bargiota, E.[Eleftheria],
Krinidis, S.[Stelios],
Papadimitriou, K.[Kimon],
Manglis, A.[Angelos],
Fourkiotou, A.[Anastasia],
Tzovaras, D.[Dimitrios],
iblueCulture: Data Streaming and Object Detection in a Real-Time
Video Streaming Underwater System,
RS(16), No. 13, 2024, pp. 2254.
DOI Link
2407
BibRef
Chen, L.[Long],
Li, T.[Tengyue],
Zhou, A.[Andy],
Wang, S.K.[Sheng-Ke],
Dong, J.Y.[Jun-Yu],
Zhou, H.Y.[Hui-Yu],
Underwater object detection in noisy imbalanced datasets,
PR(155), 2024, pp. 110649.
Elsevier DOI Code:
WWW Link.
2408
Underwater object detection, Imbalanced detection,
Noise removal, Factor-agnostic gradient re-weighting
BibRef
Li, G.Q.[Guan-Qing],
Huang, S.X.[Sheng-Xiang],
Yin, Z.[Zhi],
Zheng, N.S.[Nan-Shan],
Zhang, K.F.[Ke-Fei],
Analysis of the Influence of Refraction-Parameter Deviation on
Underwater Stereo-Vision Measurement with Flat Refraction Interface,
RS(16), No. 17, 2024, pp. 3286.
DOI Link
2409
BibRef
Chen, L.[Long],
Xie, Y.Z.[Yun-Zhou],
Li, Y.X.[Ya-Xin],
Xu, Q.[Qi],
Dong, J.Y.[Jun-Yu],
CWSCNet: Channel-Weighted Skip Connection Network for Underwater
Object Detection,
IP(33), 2024, pp. 5206-5218.
IEEE DOI
2410
Feature extraction, Object detection, Convolution, Standards,
Training, Semantics, Decoding, Underwater object detection,
feature selection
BibRef
Hou, X.[Xianghao],
Hua, W.S.[Wei-Si],
Chen, Y.X.[Yu-Xuan],
Yang, Y.X.[Yi-Xin],
A Novel Beam-Domain Direction-of-Arrival Tracking Algorithm for an
Underwater Target,
RS(16), No. 21, 2024, pp. 4074.
DOI Link
2411
BibRef
Xu, R.[Ruishen],
Zhu, D.[Daqi],
Chen, M.Z.[Ming-Zhi],
A novel underwater object detection enhanced algorithm based on
YOLOv5-MH,
IET-IPR(18), No. 12, 2024, pp. 3415-3429.
DOI Link
2411
computer vision, image enhancement, object detection
BibRef
Li, L.[Liang],
Li, Y.P.[Yi-Ping],
Wang, H.L.[Hai-Lin],
Yue, C.H.[Cheng-Hai],
Gao, P.Y.[Pei-Yan],
Wang, Y.L.[Yu-Liang],
Feng, X.S.[Xi-Sheng],
Side-Scan Sonar Image Generation Under Zero and Few Samples for
Underwater Target Detection,
RS(16), No. 22, 2024, pp. 4134.
DOI Link
2412
BibRef
Xie, Z.R.[Zhuo-Ran],
Yang, M.[Miao],
Shen, M.J.[Meng-Jiao],
Qiu, Y.[Yuquan],
Wang, X.Y.[Xin-Yu],
FIOD-VUE: Focusing on Invariant Information in Object Detection of
Varying Underwater Environment,
CirSysVideo(34), No. 11, November 2024, pp. 10743-10752.
IEEE DOI Code:
WWW Link.
2412
Frequency-domain analysis, Object detection, Feature extraction,
Adaptation models, Training, Filters, Image color analysis, frequency
BibRef
Hua, X.[Xia],
Cui, X.P.[Xiao-Peng],
Xu, X.H.[Xing-Hua],
Qiu, S.H.[Shao-Hua],
Li, Z.[Zhong],
Weakly Supervised Underwater Object Real-time Detection Based on
High-resolution Attention Class Activation Mapping and Category
Hierarchy,
PR(159), 2025, pp. 111111.
Elsevier DOI
2412
Underwater image, weakly supervised object detection,
hierarchical network, Class Activation Mapping, network attention
BibRef
Xu, H.[Huipu],
Zhang, M.[Meixiang],
Li, Y.Z.[Yong-Zhi],
GLIC: Underwater target detection based on global-local information
coupling and multi-scale feature fusion,
JVCIR(105), 2024, pp. 104330.
Elsevier DOI
2501
Underwater object detection, Spatial pyramid pooling,
Global-local information coupling, Multi-scale feature fusion
BibRef
Avanthey, L.[Loïca],
Beaudoin, L.[Laurent],
Dense In Situ Underwater 3D Reconstruction by Aggregation of
Successive Partial Local Clouds,
RS(16), No. 24, 2024, pp. 4737.
DOI Link
2501
BibRef
Kapoor, M.[Meghna],
Prummel, W.[Wieke],
Giraldo, J.H.[Jhony H.],
Subudhi, B.N.[Badri Narayan],
Zakharova, A.[Anastasia],
Bouwmans, T.[Thierry],
Bansal, A.[Ankur],
Graph-based Moving Object Segmentation for underwater videos using
semi-supervised learning,
CVIU(252), 2025, pp. 104290.
Elsevier DOI
2502
Graph learning, Semi-supervised learning,
Underwater object segmentation, Deep learning
BibRef
Li, H.Y.[Huan-Yu],
Wang, H.[Hao],
Zhang, Y.[Ying],
Li, L.[Li],
Ren, P.[Peng],
Underwater image captioning: Challenges, models, and datasets,
PandRS(220), 2025, pp. 440-453.
Elsevier DOI Code:
WWW Link.
2502
Underwater image captioning models,
Underwater image captioning datasets, Image degradation, Meta-learning
BibRef
Saleem, A.[Ashraf],
Awad, A.[Ali],
Paheding, S.[Sidike],
Lucas, E.[Evan],
Havens, T.C.[Timothy C.],
Esselman, P.C.[Peter C.],
Understanding the Influence of Image Enhancement on Underwater Object
Detection: A Quantitative and Qualitative Study,
RS(17), No. 2, 2025, pp. 185.
DOI Link
2502
BibRef
Rong, T.[Tian],
Wang, Y.H.[Yu-Hang],
Zhu, Q.G.[Qi-Guang],
Wang, C.X.[Chen-Xu],
Zhang, Y.C.[Yan-Chao],
Li, J.F.[Jian-Feng],
Zhou, Z.Q.[Zhi-Quan],
Luo, Q.H.[Qing-Hua],
Sequential Multimodal Underwater Single-Photon Lidar Adaptive Target
Reconstruction Algorithm Based on Spatiotemporal Sequence Fusion,
RS(17), No. 2, 2025, pp. 295.
DOI Link
2502
BibRef
Jin, J.H.[Jian-Hui],
Jiang, Q.P.[Qiu-Ping],
Wu, Q.Y.[Qing-Yuan],
Xu, B.W.[Bin-Wei],
Cong, R.M.[Run-Min],
Underwater Salient Object Detection via Dual-Stage Self-Paced
Learning and Depth Emphasis,
CirSysVideo(35), No. 3, March 2025, pp. 2147-2160.
IEEE DOI Code:
WWW Link.
2503
Training, Feature extraction, Degradation, Transformers,
Object detection, Iterative methods, Adaptation models,
depth emphasis
BibRef
Hong, L.[Lin],
Wang, X.[Xin],
Zhang, G.[Gan],
Zhao, M.[Ming],
USOD10K: A New Benchmark Dataset for Underwater Salient Object
Detection,
IP(34), 2025, pp. 1602-1615.
IEEE DOI Code:
WWW Link.
2503
Visualization, Benchmark testing, Task analysis, Transformers,
Object detection, Convolution, Decoding,
baseline
BibRef
Chen, J.[Jun],
Quan, W.T.[Wen-Ting],
He, X.Q.[Xian-Qiang],
Xu, M.[Ming],
Li, C.[Caipin],
Pan, D.[Delu],
Modeling the satellite instrument visibility range for detecting
underwater targets,
PandRS(222), 2025, pp. 64-78.
Elsevier DOI
2503
Contrast threshold, Visibility range, Satellite instrument, Underwater targets
BibRef
Yang, J.[Jinghe],
Gong, M.M.[Ming-Ming],
Pu, Y.[Ye],
Physics-informed Knowledge Transfer for Underwater Monocular Depth
Estimation,
ECCV24(LXXI: 449-465).
Springer DOI
2412
BibRef
Saoud, L.S.[Lyes Saad],
Niu, Z.W.[Zhen-Wei],
Seneviratne, L.[Lakmal],
Hussain, I.[Irfan],
Real-Time and Resource-Efficient Multi-Scale Adaptive Robotics Vision
for Underwater Object Detection and Domain Generalization,
ICIP24(3917-3923)
IEEE DOI Code:
WWW Link.
2411
YOLO, Training, Technological innovation, Accuracy, Source coding,
Robustness, Real-time systems, Robotic Vision, Marine Robotics
BibRef
Nissar, M.[Mehvish],
Subudhi, B.N.[Badri Narayan],
Jakhetiya, V.[Vinit],
Mishra, A.K.[Amit Kumar],
Underwater Change Detection Using Multiple Sampling-Based
Probabilistic Learner and Feature Preservance Discriminator,
ICIP24(3924-3930)
IEEE DOI
2411
Training, Water, Surveillance, Scattering, Object detection, Turbidity,
Feature extraction, Underwater object detection, deep learning,
multi-level feature-preserving
BibRef
Liang, X.[Xutao],
Song, P.[Pinhao],
Excavating RoI Attention for Underwater Object Detection,
ICIP22(2651-2655)
IEEE DOI
2211
Deep learning, Image coding, Head, Object detection, Detectors,
Feature extraction, Object Detection, Underwater, Attention, Vision Transformer
BibRef
Liu, H.,
Song, P.,
Ding, R.,
Towards Domain Generalization In Underwater Object Detection,
ICIP20(1971-1975)
IEEE DOI
2011
Training, Detectors, Feature extraction, Task analysis,
Object detection, Biological system modeling, Semantics,
domain invariance
BibRef
Fan, B.J.[Bao-Jie],
Chen, W.[Wei],
Cong, Y.[Yang],
Tian, J.D.[Jian-Dong],
Dual Refinement Underwater Object Detection Network,
ECCV20(XX:275-291).
Springer DOI
2011
BibRef
Zhang, L.[Lu],
Yang, X.[Xu],
Liu, Z.Y.[Zhi-Yong],
Qi, L.[Lu],
Zhou, H.[Hao],
Chiu, C.[Charles],
Single Shot Feature Aggregation Network for Underwater Object
Detection,
ICPR18(1906-1911)
IEEE DOI
1812
Feature extraction, Object detection, Detectors, Task analysis,
Training, Semantics, Convolutional neural networks
BibRef
Rekik, F.[Farah],
Ayedi, W.[Walid],
Jallouli, M.[Mohamed],
Performance Evaluation of Multiscale Covariance Descriptor in
Underwater Object Detection,
CIAP17(II:258-266).
Springer DOI
1711
BibRef
Cobb, J.T.,
Stack, J.R.,
In Situ Adaptive Feature Extraction for Underwater Target
Classification,
AIPR07(42-47).
IEEE DOI
0710
BibRef
Chapter on Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar continues in
Color Sensors, Sensor Models .