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We introduce the task of 3D visual grounding in large-scale dynamic scenes based on natural linguistic descriptions and online captured multi-modal visual data, including 2D images and 3D LiDAR point clouds.
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Mao, J., Huang, J., Toshev, A., Camburu, O., Yuille, A.L., Murphy, K.: Generation and comprehension of unambiguous object descriptions. In: CVPR. pp. 11–20 (2016)
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Nagaraja, V.K., Morariu, V.I., Davis, L.S.: Modeling context between objects for referring expression understanding. In: ECCV. pp. 792–807. Springer (2016)
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Yu, L., Poirson, P., Yang, S., Berg, A.C., Berg, T.L.: Modeling context in referring expressions. In: ECCV. pp. 69–85. Springer (2016)
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De Vries, H., Strub, F., Chandar, S., Pietquin, O., Larochelle, H., Courville, A.: Guesswhat?! visual object discovery through multi-modal dialogue. pp. 5503–5512 (2017)
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Hu, R., Rohrbach, M., etc.: Modeling relationships in referential expressions with compositional modular networks. In: CVPR. pp. 1115–1124 (2017)
2017
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Krishna, R., Zhu, Y., Groth, O., Johnson, J., Hata, K., Kravitz, J., Chen, S., Kalantidis, Y., Li, L.J., Shamma, D.A., et al.: Visual genome: Connecting language and vision using crowdsourced dense image annotations. International journal of computer vision 123
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Qi, C.R., Yi, L., Su, H., Guibas, L.J.: Pointnet++: Deep hierarchical feature learning on point sets in a metric space. Advances in neural information processing systems 30
2017
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Rohrbach, A., Rohrbach, M., Tang, S., Joon Oh, S., Schiele, B.: Generating descriptions with grounded and co-referenced people. In: CVPR. pp. 4979–4989 (2017)
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2018
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Qi, C.R., Liu, W., Wu, C., Su, H., Guibas, L.J.: Frustum pointnets for 3d object detection from rgb-d data. In: CVPR. pp. 918–927 (2018)
2018
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Yu, L., Lin, Z., Shen, X., Yang, J., Lu, X., Bansal, M., Berg, T.L.: Mattnet: Modular attention network for referring expression comprehension. In: CVPR (June 2018)
2018
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Behley, J., Garbade, M., Milioto, A., Quenzel, J., Behnke, S., Stachniss, C., Gall, J.: Semantickitti: A dataset for semantic scene understanding of lidar sequences. In: Proceedings of the IEEE/CVF international conference on computer vision. pp. 9297–9307 (2019)
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Liu, R., Liu, C., Bai, Y., Yuille, A.L.: Clevr-ref+: Diagnosing visual reasoning with referring expressions. In: CVPRn. pp. 4185–4194 (2019)
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Lu, J., Batra, D., Parikh, D., Lee, S.: Vilbert: Pretraining task-agnostic visiolinguistic representations for vision-and-language tasks. In: Wallach, H., Larochelle, H., Beygelzimer, A., d'Alché-Buc, F., Fox, E., Garnett, R. (eds.) Advances in Neural Information Processing Systems. vol. 32. Curran Associates, Inc. (2019), https://proceedings.neurips.cc/paper/2019/file/c74d97b01eae257e44aa9d5bade97baf-Paper.pdf
2019
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Ott, M., Edunov, S., Baevski, A., Fan, A., Gross, S., Ng, N., Grangier, D., Auli, M.: fairseq: A fast, extensible toolkit for sequence modeling. In: Proceedings of NAACL-HLT 2019: Demonstrations (2019)
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Sindagi, V.A., Zhou, Y., Tuzel, O.: Mvx-net: Multimodal voxelnet for 3d object detection. In: ICRA. pp. 7276–7282. IEEE (2019)
2019
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2019
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Wang, P., Wu, Q., Cao, J., Shen, C., Gao, L., Hengel, A.v.d.: Neighbourhood watch: Referring expression comprehension via language-guided graph attention networks. In: CVPR. pp. 1960–1968 (2019)
2019
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Yang, S., Li, G., Yu, Y.: Dynamic graph attention for referring expression comprehension. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 4644–4653 (2019)
2019
Cited alongside, same era.
Yang, Z., etc.: A fast and accurate one-stage approach to visual grounding. In: ICCV (October 2019)
2019
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Zhou, L., Kalantidis, Y., etc.: Grounded video description. In: CVPR. pp. 6578–6587 (2019)
2019
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Achlioptas, P., Abdelreheem, A., Xia, F., Elhoseiny, M., Guibas, L.: Referit3d: Neural listeners for fine-grained 3d object identification in real-world scenes. In: European Conference on Computer Vision. pp. 422–440. Springer (2020)
2020
Cited alongside, same era.
Caesar, H., Bankiti, V., Lang, A.H., Vora, S., Liong, V.E., Xu, Q., Krishnan, A., Pan, Y., Baldan, G., Beijbom, O.: nuscenes: A multimodal dataset for autonomous driving. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition. pp. 11621–11631 (2020)
Zhuang, Z., Li, R., Jia, K., Wang, Q., Li, Y., Tan, M.: Perception-aware multi-sensor fusion for 3d lidar semantic segmentation. In: ICCV. pp. 16280–16290 (October 2021)
2021
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Bai, X., Hu, Z., Zhu, X., Huang, Q., Chen, Y., Fu, H., Tai, C.L.: Transfusion: Robust lidar-camera fusion for 3d object detection with transformers. In: CVPR. pp. 1090–1099 (2022)
2022
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Cai, D., Zhao, L., Zhang, J., Sheng, L., Xu, D.: 3djcg: A unified framework for joint dense captioning and visual grounding on 3d point clouds. In: CVPR. pp. 16464–16473 (2022)
2022
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2022
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2020
Cited alongside, same era.
Chen, D.Z., Chang, A.X., Nießner, M.: Scanrefer: 3d object localization in rgb-d scans using natural language. In: ECCV. pp. 202–221. Springer (2020)
2020
Cited alongside, same era.
Liao, Y., Liu, S., Li, G., Wang, F., Chen, Y., Qian, C., Li, B.: A real-time cross-modality correlation filtering method for referring expression comprehension. In: CVPR. pp. 10880–10889 (2020)
2020
Cited alongside, same era.
Qi, C.R., Chen, X., Litany, O., Guibas, L.J.: Imvotenet: Boosting 3d object detection in point clouds with image votes. In: CVPR. pp. 4404–4413 (2020)
2020
Cited alongside, same era.
Vora, S., Lang, e.: Pointpainting: Sequential fusion for 3d object detection. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition. pp. 4604–4612 (2020)
2020
Cited alongside, same era.
Yang, Z., Chen, T., Wang, L., Luo, J.: Improving one-stage visual grounding by recursive sub-query construction. In: ECCV. pp. 387–404. Springer (2020)
2020
Cited alongside, same era.
Cho, J., Lei, J., Tan, H., Bansal, M.: Unifying vision-and-language tasks via text generation. In: ICML. pp. 1931–1942. PMLR (2021)
2021
Cited alongside, same era.
Deng, J., Yang, Z., Chen, T., Zhou, W., Li, H.: Transvg: End-to-end visual grounding with transformers. In: ICCV. pp. 1769–1779 (2021)
2021
Cited alongside, same era.
2022
Later among the works it cites.
2022
Later among the works it cites.
Cong, P., Zhu, X., Qiao, F., Ren, Y., Peng, X., Hou, Y., Xu, L., Yang, R., Manocha, D., Ma, Y.: Stcrowd: A multimodal dataset for pedestrian perception in crowded scenes. CVPR (2022)
2022
Later among the works it cites.
2022
Later among the works it cites.
Huang, S., Chen, Y., Jia, J., Wang, L.: Multi-view transformer for 3d visual grounding. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 15524–15533 (2022)
2022
Later among the works it cites.
Kolmet, M., Zhou, Q., Ošep, A., Leal-Taixé, L.: Text2pos: Text-to-point-cloud cross-modal localization. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 6687–6696 (2022)
2022
Later among the works it cites.
Li, Y., Yu, A.W., Meng, T., Caine, B., Ngiam, J., Peng, D., Shen, J., Lu, Y., Zhou, D., Le, Q.V., et al.: Deepfusion: Lidar-camera deep fusion for multi-modal 3d object detection. In: CVPR. pp. 17182–17191 (2022)
2022
Later among the works it cites.
2022
Later among the works it cites.
Luo, J., Fu, J., Kong, X., Gao, C., Ren, H., Shen, H., Xia, H., Liu, S.: 3d-sps: Single-stage 3d visual grounding via referred point progressive selection. In: CVPR. pp. 16454–16463 (2022)
2022
Later among the works it cites.
Yan, X., Gao, J., Zheng, C., Zheng, C., Zhang, R., Cui, S., Li, Z.: 2dpass: 2d priors assisted semantic segmentation on lidar point clouds. In: ECCV (2022)
2022
Later among the works it cites.
2022
Later among the works it cites.
Chen, Z., Hu, R., Chen, X., Nießner, M., Chang, A.X.: Unit3d: A unified transformer for 3d dense captioning and visual grounding. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 18109–18119 (2023)
2023
Closest in time.
Wu, Y., Cheng, X., Zhang, R., Cheng, Z., Zhang, J.: Eda: Explicit text-decoupling and dense alignment for 3d visual grounding. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 19231–19242 (2023)
2023
Closest in time.
Xu, Y., Cong, P., Yao, Y., Chen, R., Hou, Y., Zhu, X., He, X., Yu, J., Ma, Y.: Human-centric scene understanding for 3d large-scale scenarios. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 20349–20359 (2023)
2023
Closest in time.
Zhang, Y., Gong, Z., Chang, A.X.: Multi3drefer: Grounding text description to multiple 3d objects. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 15225–15236 (2023)
2023
Closest in time.
Zhu, Z., Ma, X., Chen, Y., Deng, Z., Huang, S., Li, Q.: 3d-vista: Pre-trained transformer for 3d vision and text alignment. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 2911–2921 (2023)
2023
Closest in time.