| Ga-net: Guided aggregation net for end-to-end stereo matching F Zhang, V Prisacariu, R Yang, PHS Torr Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 819 | 2019 |
| Hypergraph convolution and hypergraph attention S Bai, F Zhang, PHS Torr Pattern Recognition 110, 107637, 2021 | 573 | 2021 |
| Deep FusionNet for Point Cloud Semantic Segmentation F Zhang, J Fang, B Wah, P Torr Europe Conference on Computer Vision (ECCV), 2020 | 189 | 2020 |
| Domain-invariant Stereo Matching Networks F Zhang, X Qi, R Yang, V Prisacariu, B Wah, P Torr Europe Conference on Computer Vision (ECCV), 2020 | 180 | 2020 |
| Augmented lidar simulator for autonomous driving J Fang, D Zhou, F Yan, T Zhao, F Zhang, Y Ma, L Wang, R Yang IEEE Robotics and Automation Letters 5 (2), 1931-1938, 2020 | 177* | 2020 |
| Separable Flow: Learning Motion Cost Volumes for Optical Flow Estimation F Zhang, OJ Woodford, VA Prisacariu, PHS Torr Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 112 | 2021 |
| Segment graph based image filtering: fast structure-preserving smoothing F Zhang, L Dai, S Xiang, X Zhang Proceedings of the IEEE International Conference on Computer Vision, 361-369, 2015 | 69 | 2015 |
| S-NeRF: Neural Radiance Fields for Street Views Z Xie, J Zhang, W Li, F Zhang, L Zhang International Conference on Learning Representations (ICLR), 2023 | 63 | 2023 |
| Instance segmentation of lidar point clouds F Zhang, C Guan, J Fang, S Bai, R Yang, P Torr, V Prisacariu International Conference on Robotics and Automation (ICRA), 2020 | 62 | 2020 |
| PM-PM: PatchMatch with Potts model for object segmentation and stereo matching S Xu, F Zhang, X He, X Shen, X Zhang IEEE Transactions on Image Processing 24 (7), 2182-2196, 2015 | 55 | 2015 |
| Fundamental principles on learning new features for effective dense matching F Zhang, BW Wah IEEE Transactions on Image Processing 27 (2), 822-836, 2017 | 49 | 2017 |
| Looking beyond single images for contrastive semantic segmentation learning F Zhang, P Torr, R Ranftl, S Richter Advances in neural information processing systems 34, 3285-3297, 2021 | 39 | 2021 |
| Fully connected guided image filtering L Dai, M Yuan, F Zhang, X Zhang Proceedings of the IEEE International Conference on Computer Vision, 352-360, 2015 | 38 | 2015 |
| NeRF-LiDAR: Generating Realistic LiDAR Point Clouds with Neural Radiance Fields J Zhang, F Zhang, S Kuang, L Zhang AAAI Conference on Artificial Intelligence (AAAI), 2024 | 23 | 2024 |
| Unsupervised Contrastive Domain Adaptation for Semantic Segmentation F Zhang, V Koltun, P Torr, R Ranftl, SR Richter arXiv preprint arXiv:2204.08399, 2022 | 13 | 2022 |
| Supplementary Meta-Learning: Towards a Dynamic Model for Deep Neural Networks F Zhang, BW Wah Proceedings of the IEEE International Conference on Computer Vision, 4344-4353, 2017 | 7 | 2017 |
| Direct3D: Scalable Image-to-3D Generation via 3D Latent Diffusion Transformer S Wu, Y Lin, F Zhang, Y Zeng, J Xu, P Torr, X Cao, Y Yao arXiv preprint arXiv:2405.14832, 2024 | 3 | 2024 |
| Method and device for optimizing simulation data, and computer-readable storage medium G Chenye, F Zhang, R Yang, L Wang, Y Ma US Patent App. 16/508,903, 2020 | 3* | 2020 |
| Single-view Neural Radiance Fields with Depth Teacher Y Chen, C Gu, F Zhang, L Zhang arXiv preprint arXiv:2303.09952, 2023 | 2 | 2023 |
| Obstacle distribution simulation method and device based on multiple models, and storage medium J Fang, F Yan, F Zhang, R Yang, L Wang, Y Ma US Patent 10,984,588, 2021 | | 2021 |
