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Wireless extended reality (XR) has attracted wide attentions as a promising technology to improve users' mobility and quality of experience.
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2010
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G. J. Sullivan, J.-R. Ohm, W.-J. Han, and T. Wiegand, “Overview of the high efficiency video coding (hevc) standard,” IEEE Trans. Circuits Syst. Video Technol. , vol. 22, no. 12, pp. 1649–1668, 2012
2012
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M. Andriluka, L. Pishchulin, P. Gehler, and B. Schiele, “2d human pose estimation: New benchmark and state of the art analysis,” in Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognit. , 2014, pp. 3686–3693
2014
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2014
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L. Wang, H. Lu, X. Ruan, and M.-H. Yang, “Deep networks for saliency detection via local estimation and global search,” in Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognit. , Jun. 2015, pp. 3183–3192
2015
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2016
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2016
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A. Tewari, M. Zollhofer, H. Kim, P. Garrido, F. Bernard, P. Perez, and C. Theobalt, “MoFA: Model-based deep convolutional face autoencoder for unsupervised monocular reconstruction,” in Proc. IEEE Int. Conf. Comput. Vis. Workshops , 2017, pp. 1274–1283
2017
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2017
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N. Farsad, M. Rao, and A. Goldsmith, “Deep learning for joint source-channel coding of text,” in Proc. IEEE Int. Conf. Acoust. Speech Signal Process. (ICASSP) . IEEE, 2018, pp. 2326–2330
2018
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Y. Blau and T. Michaeli, “The perception-distortion tradeoff,” in Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognit. , 2018, pp. 6228–6237
2018
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A. Kanazawa, M. J. Black, D. W. Jacobs, and J. Malik, “End-to-end recovery of human shape and pose,” in Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognit. , 2018, pp. 7122–7131
2018
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A. Dai, D. Ritchie, M. Bokeloh, S. Reed, J. Sturm, and M. Nießner, “Scancomplete: Large-scale scene completion and semantic segmentation for 3D scans,” in Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognit. , Jun 2018, pp. 4578–4587
2018
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R. Zhang, P. Isola, A. A. Efros, E. Shechtman, and O. Wang, “The unreasonable effectiveness of deep features as a perceptual metric,” in Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognit. , Jun. 2018, pp. 586–595
2018
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F. Mentzer, E. Agustsson, M. Tschannen, R. Timofte, and L. Van Gool, “Conditional probability models for deep image compression,” in Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognit. , Jun. 2018, pp. 4394–4402
2018
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M. Li, W. Zuo, S. Gu, D. Zhao, and D. Zhang, “Learning convolutional networks for content-weighted image compression,” in Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognit. , 2018, pp. 3214–3223
2018
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E. Bourtsoulatze, D. B. Kurka, and D. Gündüz, “Deep joint source-channel coding for wireless image transmission,” IEEE Trans. Cogn. Commun. Netw. , vol. 5, no. 3, pp. 567–579, 2019
2019
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H. Xie, Z. Qin, and G. Y. Li, “Task-oriented multi-user semantic communications for VQA,” IEEE Wirel. Commun. Lett. , vol. 11, no. 3, pp. 553–557, 2021
2021
Later among the works it cites.
F. Zhan, C. Zhang, Y. Yu, Y. Chang, S. Lu, F. Ma, and X. Xie, “Emlight: Lighting estimation via spherical distribution approximation,” in Proc. Conf. AAAI Artif. Intell. , vol. 35, no. 4, 2021, pp. 3287–3295
2021
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J. Sun, Y. Xie, L. Chen, X. Zhou, and H. Bao, “Neuralrecon: Real-time coherent 3d reconstruction from monocular video,” in Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognit. , Jun. 2021, pp. 15 598–15 607
2021
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I. F. Akyildiz and H. Guo, “Wireless extended reality (xr): Challenges and new research directions,” ITU J. Future Evol. Technol , vol. 3, pp. 1–15, 2022
2022
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X. Zhang, Q. Li, H. Mo, W. Zhang, and W. Zheng, “End-to-end hand mesh recovery from a monocular RGB image,” in Proc. IEEE Int. Conf. Comput. Vis. , 2019, pp. 2354–2364
2019
Cited alongside, same era.
M. Jankowski, D. Gündüz, and K. Mikolajczyk, “Wireless image retrieval at the edge,” IEEE J. Sel. Areas Commun. , vol. 39, no. 1, pp. 89–100, 2020
2020
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F. Mentzer, G. D. Toderici, M. Tschannen, and E. Agustsson, “High-fidelity generative image compression,” Adv. Neural Inf. Process Syst. , vol. 33, pp. 11 913–11 924, 2020
2020
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O. Wiles, G. Gkioxari, R. Szeliski, and J. Johnson, “Synsin: End-to-end view synthesis from a single image,” in Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognit. , Jun. 2020, pp. 7467–7477
2020
Cited alongside, same era.
2020
Cited alongside, same era.
2021
Cited alongside, same era.
H. Xie, Z. Qin, G. Y. Li, and B.-H. Juang, “Deep learning enabled semantic communication systems,” IEEE Trans. Signal Process. , vol. 69, pp. 2663–2675, Apr. 2021
2021
Cited alongside, same era.
Z. Weng and Z. Qin, “Semantic communication systems for speech transmission,” IEEE J. Sel. Areas Commun. , vol. 39, no. 8, pp. 2434–2444, 2021
2021
Cited alongside, same era.
D. G. Morín, P. Pérez, and A. G. Armada, “Toward the distributed implementation of immersive augmented reality architectures on 5G networks,” IEEE Commun. Mag. , vol. 60, no. 2, pp. 46–52, Feb. 2022
2022
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2022
Later among the works it cites.
2022
Later among the works it cites.
J. Dai, S. Wang, K. Tan, Z. Si, X. Qin, K. Niu, and P. Zhang, “Nonlinear transform source-channel coding for semantic communications,” IEEE J. Sel. Areas Commun. , vol. 40, no. 8, pp. 2300–2316, 2022
2022
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D. Huang, F. Gao, X. Tao, Q. Du, and J. Lu, “Toward semantic communications: Deep learning-based image semantic coding,” IEEE J. Sel. Areas Commun. , vol. 41, no. 1, pp. 55–71, 2022
2022
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P. Jiang, C.-K. Wen, S. Jin, and G. Y. Li, “Wireless semantic communications for video conferencing,” IEEE J. Sel. Areas Commun. , vol. 41, no. 1, pp. 230–244, 2022
2022
Later among the works it cites.
H. Xie, Z. Qin, X. Tao, and K. B. Letaief, “Task-oriented multi-user semantic communications,” IEEE J. Sel. Areas Commun. , vol. 40, no. 9, pp. 2584–2597, July 2022
2022
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S. Wang, S. Yang, H. Su, C. Zhao, C. Xu, F. Qian, N. Wang, and Z. Xu, “Robust saliency-driven quality adaptation for mobile 360-degree video streaming,” IEEE Trans. Mob. Comput. , Jan. 2023
2023
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