VisDrone-DET2019: The vision meets drone object detection in image challenge results D Du, P Zhu, L Wen, X Bian, H Lin, Q Hu, T Peng, J Zheng, X Wang, ... Proceedings of the IEEE/CVF international conference on computer vision …, 2019 | 423 | 2019 |
Spatial attention for multi-scale feature refinement for object detection H Wang, Z Wang, M Jia, A Li, T Feng, W Zhang, L Jiao Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 38 | 2019 |
Large-scale semantic 3-D reconstruction: Outcome of the 2019 IEEE GRSS data fusion contest—Part B Y Lian, T Feng, J Zhou, M Jia, A Li, Z Wu, L Jiao, M Brown, G Hager, ... IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2020 | 30 | 2020 |
A dense Pointnet++ architecture for 3D point cloud semantic segmentation Y Lian, T Feng, J Zhou IGARSS 2019-2019 IEEE International Geoscience and Remote Sensing Symposium …, 2019 | 29 | 2019 |
Clustering based Point Cloud Representation Learning for 3D Analysis T Feng, W Wang, X Wang, Y Yang, Q Zheng Proceedings of the IEEE/CVF international conference on computer vision …, 2023 | 23 | 2023 |
A novel object re-track framework for 3D point clouds T Feng, L Jiao, H Zhu, L Sun Proceedings of the 28th ACM International Conference on Multimedia (ACMMM …, 2020 | 14 | 2020 |
Interpretable3D: An Ad-Hoc Interpretable Classifier for 3D Point Clouds T Feng, R Quan, X Wang, W Wang, Y Yang Proceedings of the AAAI Conference on Artificial Intelligence 38, 1761, 2024 | 10 | 2024 |
LSK3DNet: Towards Effective and Efficient 3D Perception with Large Sparse Kernels T Feng, W Wang, F Ma, Y Yang CVPR 2024, 2024 | 4 | 2024 |
Shape2Scene: 3D Scene Representation Learning Through Pre-training on Shape Data T Feng, W Wang, R Quan, Y Yang The 18th European Conference on Computer Vision ECCV 2024, 2024 | | 2024 |
LSK3DNet: Towards Effective and Efficient 3D Perception with Large Sparse Kernels Supplemental Material T Feng, W Wang, F Ma, Y Yang | | |
Clustering based Point Cloud Representation Learning for 3D Analysis Supplemental Material T Feng, W Wang, X Wang, Y Yang, Q Zheng | | |