| Fbnet: Hardware-aware efficient convnet design via differentiable neural architecture search B Wu, X Dai, P Zhang, Y Wang, F Sun, Y Wu, Y Tian, P Vajda, Y Jia, ... Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2019 | 1589 | 2019 |
| Squeezeseg: Convolutional neural nets with recurrent crf for real-time road-object segmentation from 3d lidar point cloud B Wu, A Wan, X Yue, K Keutzer 2018 IEEE international conference on robotics and automation (ICRA), 1887-1893, 2018 | 1070 | 2018 |
| Squeezesegv2: Improved model structure and unsupervised domain adaptation for road-object segmentation from a lidar point cloud B Wu, X Zhou, S Zhao, X Yue, K Keutzer 2019 international conference on robotics and automation (ICRA), 4376-4382, 2019 | 785 | 2019 |
| Squeezedet: Unified, small, low power fully convolutional neural networks for real-time object detection for autonomous driving B Wu, F Iandola, PH Jin, K Keutzer Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 767 | 2017 |
| Visual transformers: Token-based image representation and processing for computer vision B Wu, C Xu, X Dai, A Wan, P Zhang, Z Yan, M Tomizuka, J Gonzalez, ... arXiv preprint arXiv:2006.03677, 2020 | 626 | 2020 |
| Unbiased teacher for semi-supervised object detection YC Liu, CY Ma, Z He, CW Kuo, K Chen, P Zhang, B Wu, Z Kira, P Vajda arXiv preprint arXiv:2102.09480, 2021 | 520 | 2021 |
| Squeezesegv3: Spatially-adaptive convolution for efficient point-cloud segmentation C Xu, B Wu, Z Wang, W Zhan, P Vajda, K Keutzer, M Tomizuka Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 476 | 2020 |
| Shift: A zero flop, zero parameter alternative to spatial convolutions B Wu, A Wan, X Yue, P Jin, S Zhao, N Golmant, A Gholaminejad, ... Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 454 | 2018 |
| Open-vocabulary semantic segmentation with mask-adapted clip F Liang, B Wu, X Dai, K Li, Y Zhao, H Zhang, P Zhang, P Vajda, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 397 | 2023 |
| Squeezenext: Hardware-aware neural network design A Gholami, K Kwon, B Wu, Z Tai, X Yue, P Jin, S Zhao, K Keutzer Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 376 | 2018 |
| FBNetV2: Differentiable Neural Architecture Search for Spatial and Channel Dimensions A Wan, X Dai, P Zhang, Z He, Y Tian, S Xie, B Wu, M Yu, T Xu, K Chen, ... arXiv preprint arXiv:2004.05565, 2020 | 356 | 2020 |
| Chamnet: Towards efficient network design through platform-aware model adaptation X Dai, P Zhang, B Wu, H Yin, F Sun, Y Wang, M Dukhan, Y Hu, Y Wu, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 325 | 2019 |
| Mixed precision quantization of convnets via differentiable neural architecture search B Wu, Y Wang, P Zhang, Y Tian, P Vajda, K Keutzer arXiv preprint arXiv:1812.00090, 2018 | 310 | 2018 |
| A review of single-source deep unsupervised visual domain adaptation S Zhao, X Yue, S Zhang, B Li, H Zhao, B Wu, R Krishna, JE Gonzalez, ... IEEE Transactions on Neural Networks and Learning Systems 33 (2), 473-493, 2020 | 289 | 2020 |
| A lidar point cloud generator: from a virtual world to autonomous driving X Yue, B Wu, SA Seshia, K Keutzer, AL Sangiovanni-Vincentelli Proceedings of the 2018 ACM on international conference on multimedia …, 2018 | 267 | 2018 |
| Fbnetv3: Joint architecture-recipe search using predictor pretraining X Dai, A Wan, P Zhang, B Wu, Z He, Z Wei, K Chen, Y Tian, M Yu, P Vajda, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 188* | 2021 |
| Cross-domain adaptive teacher for object detection YJ Li, X Dai, CY Ma, YC Liu, K Chen, B Wu, Z He, K Kitani, P Vajda Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 187 | 2022 |
| Synetgy: Algorithm-hardware co-design for convnet accelerators on embedded fpgas Y Yang, Q Huang, B Wu, T Zhang, L Ma, G Gambardella, M Blott, ... Proceedings of the 2019 ACM/SIGDA international symposium on field …, 2019 | 144 | 2019 |
| epointda: An end-to-end simulation-to-real domain adaptation framework for lidar point cloud segmentation S Zhao, Y Wang, B Li, B Wu, Y Gao, P Xu, T Darrell, K Keutzer Proceedings of the AAAI Conference on Artificial Intelligence 35 (4), 3500-3509, 2021 | 92 | 2021 |
| Image2point: 3d point-cloud understanding with 2d image pretrained models C Xu, S Yang, T Galanti, B Wu, X Yue, B Zhai, W Zhan, P Vajda, K Keutzer, ... European Conference on Computer Vision, 638-656, 2022 | 84 | 2022 |
Kurt KeutzerProfessor of the Graduate School, EECS, University of California, BerkeleyGeverifieerd e-mailadres voor berkeley.edu
