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This paper addresses the problem of 3D referring expression comprehension (REC) in autonomous driving scenario, which aims to ground a natural language to the targeted region in LiDAR point clouds.
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Alex H Lang, Sourabh Vora, Holger Caesar, Lubing Zhou, Jiong Yang, and Oscar Beijbom. 2019 · 2019
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nuScenes: A Multimodal Dataset for Autonomous Driving. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
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Structured Multi-Level Interaction Network for Video Moment Localization via Language Query. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition . 7026–7035
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SAT: 2D Semantics Assisted Training for 3D Visual Grounding
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Center-Based 3D Object Detection and Tracking. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) . 11784–11793
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Zhihao Yuan, Xu Yan, Yinghong Liao, Ruimao Zhang, Zhen Li, and Shuguang Cui. 2021 · 2021
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Transfusion: Robust lidar-camera fusion for 3d object detection with transformers. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition . 1090–1099
Xuyang Bai, Zeyu Hu, Xinge Zhu, Qingqiu Huang, Yilun Chen, Hongbo Fu, and Chiew-Lan Tai. 2022 · 2022
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Futr3d: A unified sensor fusion framework for 3d detection
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Autoalignv2: Deformable feature aggregation for dynamic multi-modal 3d object detection
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Learning Disentanglement with Decoupled Labels for Vision-Language Navigation. In Computer Vision–ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23–27, 2022, Proceedings, Part XXXVI . Springer, 309–329
Wenhao Cheng, Xingping Dong, Salman Khan, and Jianbing Shen. 2022 · 2022
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Bevfusion: A simple and robust lidar-camera fusion framework
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BEVFusion: Multi-Task Multi-Sensor Fusion with Unified Bird’s-Eye View Representation
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