| FoldingNet: Point cloud auto-encoder via deep grid deformation Y Yang, C Feng, Y Shen, D Tian IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 206-215, 2018 | 1518 | 2018 |
| Mining Point Cloud Local Structures by Kernel Correlation and Graph Pooling Y Shen, C Feng, Y Yang, D Tian IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 4, 2018 | 658 | 2018 |
| Geometric distortion metrics for point cloud compression D Tian, H Ochimizu, C Feng, R Cohen, A Vetro 2017 IEEE International Conference on Image Processing (ICIP), 3460-3464, 2017 | 427 | 2017 |
| CASENet: Deep Category-Aware Semantic Edge Detection Z Yu, C Feng, MY Liu, S Ramalingam IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 5964--5973, 2017 | 387 | 2017 |
| Point-Plane SLAM for Hand-Held 3D Sensors Y Taguchi, YD Jian, S Ramalingam, C Feng IEEE International Conference on Robotics and Automation (ICRA), 2013 | 286 | 2013 |
| Fast plane extraction in organized point clouds using agglomerative hierarchical clustering C Feng, Y Taguchi, VR Kamat 2014 IEEE International Conference on Robotics and Automation (ICRA), 6218-6225, 2014 | 259 | 2014 |
| Fast resampling of three-dimensional point clouds via graphs S Chen, D Tian, C Feng, A Vetro, J Kovačević IEEE Transactions on Signal Processing 66 (3), 666-681, 2017 | 258 | 2017 |
| V2X-Sim: Multi-Agent Collaborative Perception Dataset and Benchmark for Autonomous Driving Y Li, D Ma, Z An, Z Wang, Y Zhong, S Chen, C Feng IEEE Robotics and Automation Letters 7 (4), 10914-10921, 2022 | 244* | 2022 |
| Learning distilled collaboration graph for multi-agent perception Y Li, S Ren, P Wu, S Chen, C Feng, W Zhang Advances in Neural Information Processing Systems 34, 29541-29552, 2021 | 226 | 2021 |
| 3D Point Cloud Processing and Learning for Autonomous Driving: Impacting Map Creation, Localization, and Perception S Chen, B Liu, C Feng, C Vallespi-Gonzalez, C Wellington IEEE Signal Processing Magazine 38 (1), 68-86, 2020 | 226 | 2020 |
| Voxformer: Sparse voxel transformer for camera-based 3d semantic scene completion Y Li, Z Yu, C Choy, C Xiao, JM Alvarez, S Fidler, C Feng, A Anandkumar IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 9087-9098, 2023 | 220 | 2023 |
| Deep Active Learning for Civil Infrastructure Defect Detection and Classification C Feng, MY Liu, CC Kao, TY Lee Computing in Civil Engineering 2017, 298-306, 2017 | 196 | 2017 |
| LUVLi Face Alignment: Estimating Landmarks' Location, Uncertainty, and Visibility Likelihood A Kumar, TK Marks, W Mou, Y Wang, M Jones, A Cherian, T Koike-Akino, ... IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 8236-8246, 2020 | 190 | 2020 |
| Vision guided autonomous robotic assembly and as-built scanning on unstructured construction sites C Feng, Y Xiao, A Willette, W McGee, VR Kamat Automation in Construction 59, 128-138, 2015 | 183 | 2015 |
| Collaborative visualization of engineering processes using tabletop augmented reality S Dong, AH Behzadan, C Feng, VR Kamat Advances in Engineering Software 55, 45-55, 2013 | 164 | 2013 |
| Method for extracting planes from 3D point cloud sensor data C Feng, Y Taguchi, V Kamat US Patent 9,412,040 B2, 2013 | 160 | 2013 |
| Simultaneous Edge Alignment and Learning Z Yu, W Liu, Y Zou, C Feng, S Ramalingam, BVK Vijaya Kumar, J Kautz European Conference on Computer Vision (ECCV), 388-404, 2018 | 107 | 2018 |
| An Occupancy Grid Mapping enhanced visual SLAM for real-time locating applications in indoor GPS-denied environments L Xu, C Feng, VR Kamat, CC Menassa Automation in Construction 104, 230-245, 2019 | 100 | 2019 |
| DeepMapping: Unsupervised map estimation from multiple point clouds L Ding, C Feng IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 8650-8659, 2019 | 85 | 2019 |
| Siamese Anchor Proposal Network for High-Speed Aerial Tracking C Fu, Z Cao, Y Li, J Ye, C Feng 2021 IEEE International Conference on Robotics and Automation (ICRA), 510-516, 2021 | 84 | 2021 |
Yiming LiNVIDIA Research | NYU Ph.D.Email verificata su nyu.edu