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References

1 
Y. Chen , S. Liu , X. Wang , Learning continuous image representation with local implicit image function, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021URL
2 
H. Chang , Q. Ding , Face super-resolution via Restormer attention and feedback-enhanced facial prior integration, IEIE Transactions on Smart Processing & Computing, Vol. 14, No. 5, pp. 616-630, 2025DOI
3 
Z. Yan , Z. Liu , J. Li , Boosting of implicit neural representation-based image denoiser, Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2024URL
4 
Y. Yan , W. Ren , Y. Guo , R. Wang , X. Cao , Image deblurring via extreme channels prior, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 4003-4011, 2017URL
5 
M. Bertalmio , G. Sapiro , V. Caselles , C. Ballester , Image inpainting, Proceedings of ACM SIGGRAPH, pp. 417-424, 2000URL
6 
S. Ren , K. He , R. Girshick , J. Sun , Faster R-CNN: towards real-time object detection with region proposal networks, Advances in Neural Information Processing Systems (NeurIPS), 2015URL
7 
M. Allmamun , F. Akter , M. B. U. Talukdar , S. Chakraborty , J. Uddin , Drone detection and tracking using deep convolutional neural networks from real-time CCTV footage, IEIE Transactions on Smart Processing & Computing, Vol. 13, No. 4, pp. 313-321, 2024DOI
8 
J. Long , E. Shelhamer , T. Darrell , Fully convolutional networks for semantic segmentation, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015URL
9 
B. A. Lodhi , R. Ullah , S. Imran , M. Imran , B.-S. Kim , Sensenet: densely connected, fully convolutional network with bottleneck skip connection for image segmentation, IEIE Transactions on Smart Processing & Computing, Vol. 13, No. 4, pp. 328-336, 2024DOI
10 
Y. Zhou , Q. Ye , J. Qiu , Z. Li , J. Han , SceneGraphNet: neural message passing for 3D indoor scene augmentation, Proceedings of the IEEE International Conference on Computer Vision (ICCV), 2019URL
11 
J. L. Schönberger , J.-M. Frahm , Structure-from-motion revisited, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016URL
12 
C. Kwag , S. S. Hwang , Neural rendering survey targeted on speed, quality, 3D reconstruction, and editing, IEIE Transactions on Smart Processing & Computing, Vol. 14, No. 2, pp. 191-204, 2025DOI
13 
Q. Yu , Application of 3D scene reconstruction in sports public service based on pyramid lk optical flow method and ransac algorithm, IEIE Transactions on Smart Processing & Computing, Vol. 14, No. 4, pp. 457-470, 2025DOI
14 
B. Mildenhall , P. P. Srinivasan , M. Tancik , J. T. Barron , R. Ramamoorthi , R. Ng , NeRF: representing scenes as neural radiance fields for view synthesis, Proceedings of the European Conference on Computer Vision (ECCV), 2020URL
15 
L. Mescheder , M. Oechsle , M. Niemeyer , S. Nowozin , A. Geiger , Occupancy networks: learning 3D reconstruction in function space, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019URL
16 
S. Levine , C. Finn , T. Darrell , P. Abbeel , End-to-end training of deep visuomotor policies, Journal of Machine Learning Research, 2016URL
17 
C. Chen , A. Seff , A. Kornhauser , J. Xiao , Deep-driving: learning affordance for direct perception in autonomous driving, Proceedings of the IEEE International Conference on Computer Vision (ICCV), pp. 2722-2730, 2015URL
18 
J. Carmigniani , B. Furht , M. Anisetti , P. Ceravolo , E. Damiani , M. Ivkovic , Augmented reality technologies, systems and applications, Multimedia Tools and Applications, Vol. 51, No. 1, pp. 341-377, 2011DOI
19 
D. Lin , Image recognition processing technology based on virtual reality technology and adaptive feature fusion, IEIE Transactions on Smart Processing & Computing, Vol. 14, No. 6, pp. 715-727, 2025DOI
20 
C. Boje , A. Guerriero , S. Kubicki , Y. Rezgui , Towards a semantic construction digital twin: directions for future research, Automation in Construction, Vol. 114, pp. 103179, 2020DOI
21 
C. B. Choy , D. Xu , J. Gwak , K. Chen , S. Savarese , 3D-R2N2: a unified approach for single and multi-view 3D object reconstruction, Proceedings of the European Conference on Computer Vision (ECCV), pp. 628-644, 2016URL
22 
L. Liu , J. Gu , K. Z. Lin , T.-S. Chua , C. Theobalt , Neural sparse voxel fields, Advances in Neural Information Processing Systems (NeurIPS), Vol. 33, pp. 15651-15663, 2020URL
23 
S. A. Bello , S. Yu , C. Wang , J. M. Adam , J. Li , Deep learning on 3D point clouds, Remote Sensing, Vol. 12, No. 11, pp. 1729, 2020DOI
24 
D. Ulyanov , A. Vedaldi , V. Lempitsky , Deep image prior, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 9446-9454, 2018URL
25 
K. Su , M. Chen , E. Shlizerman , Inras: implicit neural representation for audio scenes, Advances in Neural Information Processing Systems (NeurIPS), Vol. 35, pp. 8144-8158, 2022URL
26 
L. Mescheder , M. Oechsle , M. Niemeyer , S. Nowozin , A. Geiger , Occupancy networks: learning 3D reconstruction in function space, Proc. IEEE/CVF Conf. on Computer Vision and Pattern Recognition (CVPR), pp. 4460-4470, 2019URL
27 
N. Rahaman , A. Baratin , D. Arpit , F. Draxler , M. Lin , F. Hamprecht , Y. Bengio , A. Courville , On the spectral bias of neural networks, Proceedings of the International Conference on Machine Learning (ICML), pp. 5301-5310, 2019URL
28 
A. F. Agarap , Deep learning using rectified linear units (ReLU), arXiv preprint arXiv:1803.08375, 2018URL
29 
V. Sitzmann , J. N. P. Martel , A. W. Bergman , D. B. Lindell , G. Wetzstein , Implicit neural representations with periodic activation functions, Advances in Neural Information Processing Systems (NeurIPS), 2020URL
30 
H. Saratchandran , S. Ramasinghe , V. Shevchenko , A. Long , S. Lucey , A sampling theory perspective on activations for implicit neural representations, arXiv preprint arXiv:2402.05427, 2024URL
31 
D. Serrano , J. Szymkowiak , P. Musialski , HOSC: a periodic activation function for preserving sharp features in implicit neural representations, arXiv preprint arXiv:2401.10967, 2024URL
32 
Z. Liu , H. Zhu , Q. Zhang , J. Fu , W. Deng , Z. Ma , Y. Guo , X. Cao , FINER: flexible spectral-bias tuning in implicit neural representation by variable-periodic activation functions, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2024URL
33 
V. Saragadam , D. LeJeune , J. Tan , G. Balakrishnan , A. Veeraraghavan , R. G. Baraniuk , WIRE: wavelet implicit neural representations, Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 18507-18516, 2023URL
34 
H. Zhu , Z. Liu , FINER++: building a family of variable-periodic functions for activating implicit neural representation, arXiv preprint arXiv:2407.19434, 2024URL
35 
S. Ko , D. Kye , K. Min , C. Eom , J. Oh , FLAIR: frequency- and locality-aware implicit neural representations, arXiv preprint arXiv:2508.13544, 2025URL
36 
M. Tancik , P. Srinivasan , B. Mildenhall , S. Fridovich-Keil , N. Raghavan , U. Singhal , R. Ramamoorthi , J. Barron , R. Ng , Fourier features let networks learn high frequency functions in low dimensional domains, Advances in Neural Information Processing Systems (NeurIPS), Vol. 33, pp. 7537-7547, 2020URL
37 
A. Rahimi , B. Recht , Random features for large-scale kernel machines, Advances in Neural Information Processing Systems (NeurIPS), 2007URL
38 
H. Zhao , Z. Gao , Y. Wang , R. Xiong , Y. Zhang , Adaptive wavelet-positional encoding for high-frequency information learning in implicit neural representation, Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), Vol. 39, No. 10, pp. 10430-10438, 2025URL
39 
Z. Shen , Y. Cheng , R. H. Chan , Trident: the non-linear trilogy for implicit neural representations, arXiv preprint arXiv:2311.13610, 2023URL
40 
A. Kazerouni , R. Azad , A. Hosseini , D. Merhof , U. Bagci , Incode: implicit neural conditioning with prior knowledge embeddings, Proceedings of the IEEE Winter Conference on Applications of Computer Vision (WACV), 2024URL
41 
Z. Liu , Y. Wang , S. Vaidya , KAN: Kolmogorov-Arnold networks, arXiv preprint arXiv:2404.19756, 2024URL
42 
M. Heidari , R. Rezaeian , R. Azad , D. Merhof , H. Soltanian-Zadeh , I. Hacihaliloglu , SL2A-INR: single-layer learnable activation for implicit neural representation, arXiv preprint arXiv:2409.10836, 2024URL
43 
Z. Liu , P. Ma , KAN 2.0: kolmogorov-arnold networks meet science, arXiv preprint arXiv:2408.10205, 2024URL
44 
J. Zuiderveld , M. Federici , E. Bekkers , Towards lightweight controllable audio synthesis with conditional implicit neural representations, Advances in Neural Information Processing Systems (NeurIPS), 2021URL
45 
W. K. Han , B. Lee , H. Cho , S. Im , K. H. Jin , Towards lossless implicit neural representation via bit plane decomposition, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2025URL
46 
K. Shi , X. Zhou , S. Gu , Improved implicit neural representation with Fourier reparameterized training, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 25985-25994, 2024URL
47 
A. W. Reed , H. Kim , R. Anirudh , K. A. Mohan , K. Champley , J. Kang , S. Jayasuriya , Dynamic CT reconstruction from limited views with implicit neural representations and parametric motion fields, Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), pp. 2258-2268, 2021URL
48 
Y. Jiang , H. M. Kwan , T. Peng , G. Gao , F. Zhang , X. Zhu , J. Sole , D. Bull , HIIF: hierarchical encoding based implicit image function for continuous super-resolution, Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2289-2299, 2025URL
49 
J. J. Park , P. Florence , J. Straub , R. Newcombe , S. Lovegrove , DeepSDF: learning continuous signed distance functions for shape representation, Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 165-174, 2019URL
50 
Y. Liu , C. Jin , ICGAN: an implicit conditioning method for interpretable feature control of neural audio synthesis, arXiv preprint arXiv:2406.07131, 2024URL
51 
V. Kuleshov , S. Z. Enam , S. Ermon , Audio super resolution using neural networks, arXiv preprint arXiv:1708.00853, 2017URL
52 
J. Lee , J. Tack , N. Lee , J. Shin , Meta-learning sparse implicit neural representations, Advances in Neural Information Processing Systems (NeurIPS), 2021URL
53 
E. Agustsson , R. Timofte , NTIRE 2017 challenge on single image super-resolution: dataset and study, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2017URL
54 
R. Timofte , S. Gu , J. Wu , L. Van Gool , L. Zhang , M.-H. Yang , M. Haris , NTIRE 2018 challenge on single image super-resolution: methods and results, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2018URL
55 
E. Kodak , Kodak lossless true color image suite, 1999URL
56 
M. Bevilacqua , A. Roumy , C. Guillemot , M. L. Alberi-Morel , Low-complexity single-image super-resolution based on nonnegative neighbor embedding, Proceedings of the British Machine Vision Conference (BMVC), 2012URL
57 
G. Wang , J. C. Ye , B. De Man , Deep learning for tomographic image reconstruction, Nature Machine Intelligence, Vol. 2, No. 12, pp. 737-748, 2020DOI
58 
T. R. Moen , B. Chen , D. R. Holmes , X. Duan , Z. Yu , L. Yu , S. Leng , J. G. Fletcher , C. H. McCollough , Low-dose CT image and projection dataset, Medical Physics, Vol. 48, No. 2, pp. 902-911, 2021URL
59 
The Stanford 3D Scanning Repository, Stanford UniversityURL
60 
B. Mildenhall , P. P. Srinivasan , R. Ortiz-Cayon , N. K. Kalantari , R. Ramamoorthi , R. Ng , A. Kar , Local light field fusion: practical view synthesis with prescriptive sampling guidelines, ACM Transactions on Graphics (TOG), Vol. 38, No. 4, pp. 1-14, 2019DOI
61 
J. Yamagishi , C. Veaux , K. MacDonald , , CSTR VCTK corpus: english multi-speaker corpus for CSTR voice cloning toolkit (version 0.92), 2019DOI
62 
V. Panayotov , G. Chen , D. Povey , S. Khudanpur , LibriSpeech: an ASR corpus based on public domain audio books, Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 5206-5210, 2015URL
63 
J. Engel , C. Resnick , A. Roberts , S. Dieleman , M. Norouzi , D. Eck , K. Simonyan , Neural audio synthesis of musical notes with Wavenet autoencoders, Proceedings of the 34th International Conference on Machine Learning (ICML), pp. 1068-1077, 2017URL
64 
Z. Wang , A. C. Bovik , H. R. Sheikh , E. P. Simoncelli , Image quality assessment: from error visibility to structural similarity, IEEE Transactions on Image Processing, Vol. 13, No. 4, pp. 600-612, 2004DOI
65 
R. Zhang , P. Isola , A. A. Efros , E. Shechtman , O. Wang , The unreasonable effectiveness of deep features as a perceptual metric, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 586-595, 2018URL
66 
H. G. Barrow , J. M. Tenenbaum , R. C. Bolles , H. C. Wolf , Parametric correspondence and chamfer matching: two new techniques for image matching, Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), 1977URL
67 
J. Le Roux , S. Wisdom , H. Erdogan , J. R. Hershey , SDR-half-baked or well done?, Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 626-630, 2019URL
68 
, Perceptual evaluation of speech quality (PESQ): an objective method for end-to-end speech quality assessment of narrow-band telephone networks and speech codecs, 2001URL
69 
C. H. Taal , R. C. Hendriks , R. Heusdens , J. Jensen , A short-time objective intelligibility measure for time-frequency weighted noisy speech, Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 4214-4217, 2010URL
70 
A. Dosovitskiy , L. Beyer , A. Kolesnikov , D. Weissenborn , X. Zhai , T. Unterthiner , M. Dehghani , M. Minderer , G. Heigold , S. Gelly , An image is worth 16x16 words: transformers for image recognition at scale, arXiv preprint arXiv:2010.11929, 2020URL
71 
A. Krizhevsky , I. Sutskever , G. E. Hinton , ImageNet classification with deep convolutional neural networks, Advances in Neural Information Processing Systems (NeurIPS), Vol. 25, 2012URL
72 
D. Grattarola , P. Vandergheynst , Generalised implicit neural representations, Advances in Neural Information Processing Systems (NeurIPS), 2022URL
73 
D. Jayasundara , S. Rajagopalan , Y. Ranasinghe , T. D. Tran , V. M. Patel , Sinr: sparsity driven compressed implicit neural representations, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2025URL
74 
W. K. Han , B. Lee , H. Cho , S. Im , K. H. Jin , Towards lossless implicit neural representation via bit plane decomposition, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2025URL