| Compositional visual generation with composable diffusion models N Liu, S Li, Y Du, A Torralba, JB Tenenbaum ECCV 2022, 2022 | 267 | 2022 |
| Learning to compose visual relations N Liu, S Li, Y Du, JB Tenenbaum, A Torralba NeurIPS 2021, 2021 | 65* | 2021 |
| Unsupervised Compositional Concepts Discovery with Text-to-Image Generative Models N Liu, Y Du, S Li, JB Tenenbaum, A Torralba ICCV 2023, 2023 | 14* | 2023 |
| FIBER: Fill-in-the-blanks as a challenging video understanding evaluation framework S Castro, R Wang, P Huang, I Stewart, O Ignat, N Liu, JC Stroud, ... ACL 2022, 2022 | 14* | 2022 |
| Sensor adversarial traits: Analyzing robustness of 3d object detection sensor fusion models W Park, N Liu, QA Chen, ZM Mao ICIP 2021, 2021 | 12 | 2021 |
| Where to: Crowd-aided path selection by selective Bayesian network C Zhang, H Zhang, W Xie, N Liu, K Wu, L Chen IEEE Transactions on Knowledge and Data Engineering, 2021 | 2 | 2021 |
| Cleaning uncertain data with crowdsourcing-a general model with diverse accuracy rates C Zhang, H Zhang, W Xie, N Liu, Q Li, D Jiang, P Lin, K Wu, L Chen IEEE Transactions on Knowledge and Data Engineering, 2020 | 2 | 2020 |
| Compositional Image Decomposition with Diffusion Models J Su, N Liu, JB Tenenbaum, Y Du | | 2023 |
| Compositional visual generation with energy-based modeling N Liu University of Illinois at Urbana-Champaign, 2023 | | 2023 |
