| Objectnet3d: A large scale database for 3d object recognition Y Xiang, W Kim, W Chen, J Ji, C Choy, H Su, R Mottaghi, L Guibas, ... European Conference on Computer Vision, 160-176, 2016 | 322 | 2016 |
| Action Genome: Actions As Compositions of Spatio-Temporal Scene Graphs J Ji, R Krishna, L Fei-Fei, JC Niebles Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 293 | 2020 |
| Few-shot video classification via temporal alignment K Cao, J Ji, Z Cao, CY Chang, JC Niebles Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 194 | 2020 |
| DeformNet: Free-form deformation network for 3d shape reconstruction from a single image A Kurenkov*, J Ji*, A Garg, V Mehta, JY Gwak, C Choy, S Savarese, ... 2018 IEEE Winter Conference on Applications of Computer Vision (WACV), 858-866, 2018 | 124 | 2018 |
| End-to-End Joint Semantic Segmentation of Actors and Actions in Video J Ji, S Buch, A Soto, J Carlos Niebles Proceedings of the European Conference on Computer Vision (ECCV), 702-717, 2018 | 48 | 2018 |
| Home Action Genome: Cooperative Compositional Action Understanding N Rai, H Chen, J Ji, R Desai, K Kozuka, S Ishizaka, E Adeli, JC Niebles Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 42 | 2021 |
| Learning temporal action proposals with fewer labels J Ji, K Cao, JC Niebles Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 36 | 2019 |
| VideoGasNet: Deep learning for natural gas methane leak classification using an infrared camera J Wang, J Ji, AP Ravikumar, S Savarese, AR Brandt Energy 238, 121516, 2022 | 32 | 2022 |
| Detecting Human-Object Relationships in Videos J Ji, R Desai, JC Niebles Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 21 | 2021 |
| Motion Inspired Unsupervised Perception and Prediction in Autonomous Driving M Najibi*, J Ji*, Y Zhou*, CR Qi, X Yan, S Ettinger, D Anguelov European Conference on Computer Vision, 424-443, 2022 | 17 | 2022 |
| New Framework for the random charging/discharging of oxide traps in HfO2 gate dielectric: ab-initio simulation and experimental evidence J Ji, Y Qiu, S Guo, R Wang, P Ren, P Hao, R Huang 2014 IEEE International Electron Devices Meeting, 21.4. 1-21.4. 4, 2014 | 13 | 2014 |
| HUM3DIL: Semi-supervised Multi-modal 3D HumanPose Estimation for Autonomous Driving A Zanfir, M Zanfir, A Gorban, J Ji, Y Zhou, D Anguelov, C Sminchisescu 6th Annual Conference on Robot Learning, 2022 | 8 | 2022 |
| An analytic model for heterojunction and homojunction tunnel FETs with 3D density of states J Wu, J Min, J Ji, Y Taur 2015 73rd Annual Device Research Conference (DRC), 249-250, 2015 | 4 | 2015 |
| Deep understanding of oxide defects for stochastic charging in nanoscale MOSFETs Y Qiu, R Wang, J Ji, R Huang 2014 Silicon Nanoelectronics Workshop (SNW), 1-2, 2014 | 4 | 2014 |
| Investigation on random charging/discharging of single oxide trap in SiO2: An ab -initio study J Ji, R Wang, Y Qiu, R Huang 2014 12th IEEE International Conference on Solid-State and Integrated …, 2014 | 2 | 2014 |
| Unsupervised 3D Perception with 2D Vision-Language Distillation for Autonomous Driving M Najibi*, J Ji*, Y Zhou, CR Qi, X Yan, S Ettinger, D Anguelov Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 1 | 2023 |
| 3D Human Keypoints Estimation From Point Clouds in the Wild Without Human Labels Z Weng, AS Gorban, J Ji, M Najibi, Y Zhou, D Anguelov Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 1 | 2023 |
| Towards Comprehensive Action Understanding in Videos J Ji Stanford University, 2021 | | 2021 |
| Theoretical investigation on hydrogen-related oxide traps in HfO2 gate dielectrics: An ab-initio study Y Zhang, P Hao, R Wang, J Ji, R Huang 2016 13th IEEE International Conference on Solid-State and Integrated …, 2016 | | 2016 |
| Towards Grasp Transfer using Shape Deformation A Kurenkov, V Mehta, J Ji, A Garg, S Savarese | | |
Juan Carlos NieblesResearch Director (Salesforce) & Adjunct Professor (Stanford University)在 cs.stanford.edu 的电子邮件经过验证
