[17] Robert F Tobler. Separating semantics from rendering: a scene graph based architecture for graphics applications. The Visual Computer, 27(6-8):687-695, 2011. 2, 3
[18] Johanna Wald, Helisa Dhamo, Nassir Navab, and Federico Tombari. Learning 3d semantic scene graphs from 3d indoor reconstructions. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 3961-3970, 2020. 2, 3, 4, 7, 8
[19] Shoulong Zhang, Aimin Hao, Hong Qin, et al. Knowledge-inspired 3d scene graph prediction in point cloud. Advances in Neural Information Processing Systems, 34:18620-18632, 2021. 2, 3
[20] Y.-T. Hu, J. Wang, R. A. Yeh, and A. G. Schwing. SAIL-VOS 3D: A Synthetic Dataset and Baselines for Object Detection and 3D Mesh Reconstruction from Video Data. In Proc. CVPR, 2021. 2, 5
[21] Grand theft auto v, 2014. 2, 4
[22] Yunze Liu, Yun Liu, Che Jiang, Kangbo Lyu, Weikang Wan, Hao Shen, Boqiang Liang, Zhoujie Fu, He Wang, and Li Yi. Hoi4d: A 4d egocentric dataset for category-level human-object interaction. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pages 21013-21022, June 2022. 2, 5
[23] Ranjay Krishna, Yuke Zhu, Oliver Groth, Justin Johnson, Kenji Hata, Joshua Kravitz, Stephanie Chen, Yannis Kalantidis, Li-Jia Li, David A Shamma, Michael Bernstein, and Li Fei-Fei. Visual genome: Connecting language and vision using crowdsourced dense image annotations. IJCV, 2017. 3
[24] Rongjie Li, Songyang Zhang, and Xuming He. Sgtr: End-to-end scene graph generation with transformer. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 19486-19496, 2022. 3
[25] Yuren Cong, Michael Ying Yang, and Bodo Rosenhahn. Reltr: Relation transformer for scene graph generation. arXiv preprint arXiv:2201.11460, 2022. 3
[26] Jingwei Ji, Ranjay Krishna, Li Fei-Fei, and Juan Carlos Niebles. Action genome: Actions as compositions of spatio-temporal scene graphs. In CVPR, 2020. 3
[27] Jinghao Wang, Zhengyu Wen, Xiangtai Li, Zujin Guo, Jingkang Yang, and Ziwei Liu. Pair then relation: Pair-net for panoptic scene graph generation. arXiv preprint arXiv:2307.08699, 2023. 3
[28] Chengyang Zhao, Yikang Shen, Zhenfang Chen, Mingyu Ding, and Chuang Gan. Textpsg: Panoptic scene graph generation from textual descriptions. In Proceedings of the IEEE/CVF International Conference on Computer Vision, pages 2839-2850, 2023. 3
[29] Zijian Zhou, Miaojing Shi, and Holger Caesar. Hilo: Exploiting high low frequency relations for unbiased panoptic scene graph generation. arXiv preprint arXiv:2303.15994, 2023. 3
[30] Julian Lorenz, Florian Barthel, Daniel Kienzle, and Rainer Lienhart. Haystack: A panoptic scene graph dataset to evaluate rare predicate classes. In Proceedings of the IEEE/CVF International Conference on Computer Vision, pages 62–70, 2023. 3
[31] Jingkang Yang, Zheng Ma, Qixun Wang, Xiaofeng Guo, Haofan Wang, Ziwei Liu, Wayne Zhang, Xing Xu, and Hai Zhang. The psg challenge: towards comprehensive scene understanding. National Science Review, 10(6):nwad126, 2023. 3
[32] Xiangtai Li, Wenwei Zhang, Jiangmiao Pang, Kai Chen, Guangliang Cheng, Yunhai Tong, and Chen Change Loy. Video k-net: A simple, strong, and unified baseline for video segmentation. In CVPR, 2022. 3
[33] Jaewon Bae, Dongmin Shin, Kangbeen Ko, Juchan Lee, and Ue-Hwan Kim. A survey on 3d scene graphs: Definition, generation and application. In Robot Intelligence Technology and Applications 7: Results from the 10th International Conference on Robot Intelligence Technology and Applications, pages 136-147. Springer, 2023. 3
[34] Ue-Hwan Kim, Jin-Man Park, Taek-Jin Song, and Jong-Hwan Kim. 3-d scene graph: A sparse and semantic representation of physical environments for intelligent agents. IEEE transactions on cybernetics, 50(12):4921-4933, 2019. 3
[35] Iro Armeni, Zhi-Yang He, JunYoung Gwak, Amir R Zamir, Martin Fischer, Jitendra Malik, and Silvio Savarese. 3d scene graph: A structure for unified semantics, 3d space, and camera. In ICCV, 2019. 3