| Acquisition of localization confidence for accurate object detection B Jiang, R Luo, J Mao, T Xiao, Y Jiang Proceedings of the European conference on computer vision (ECCV), 784-799, 2018 | 1126 | 2018 |
| The neuro-symbolic concept learner: Interpreting scenes, words, and sentences from natural supervision J Mao, C Gan, P Kohli, JB Tenenbaum, J Wu arXiv preprint arXiv:1904.12584, 2019 | 835 | 2019 |
| What can help pedestrian detection? J Mao, T Xiao, Y Jiang, Z Cao Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 351 | 2017 |
| Neural logic machines H Dong, J Mao, T Lin, C Wang, L Li, D Zhou arXiv preprint arXiv:1904.11694, 2019 | 315 | 2019 |
| Unified visual-semantic embeddings: Bridging vision and language with structured meaning representations H Wu, J Mao, Y Zhang, Y Jiang, L Li, W Sun, WY Ma Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 201 | 2019 |
| Grounding physical object and event concepts through dynamic visual reasoning Z Chen, J Mao, J Wu, KYK Wong, JB Tenenbaum, C Gan International Conference on Learning Representations, 2021 | 101* | 2021 |
| Visually grounded neural syntax acquisition H Shi, J Mao, K Gimpel, K Livescu arXiv preprint arXiv:1906.02890, 2019 | 86 | 2019 |
| Visual concept-metaconcept learning C Han, J Mao, C Gan, J Tenenbaum, J Wu Advances in Neural Information Processing Systems 32, 2019 | 77 | 2019 |
| Learning visually-grounded semantics from contrastive adversarial samples H Shi, J Mao, T Xiao, Y Jiang, J Sun arXiv preprint arXiv:1806.10348, 2018 | 54 | 2018 |
| Ns3d: Neuro-symbolic grounding of 3d objects and relations J Hsu, J Mao, J Wu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 38 | 2023 |
| Learning to act from actionless videos through dense correspondences PC Ko, J Mao, Y Du, SH Sun, JB Tenenbaum arXiv preprint arXiv:2310.08576, 2023 | 35 | 2023 |
| PDSketch: Integrated domain programming, learning, and planning J Mao, T Lozano-Pérez, J Tenenbaum, L Kaelbling Advances in Neural Information Processing Systems 35, 36972-36984, 2022 | 33* | 2022 |
| Programmatically grounded, compositionally generalizable robotic manipulation R Wang, J Mao, J Hsu, H Zhao, J Wu, Y Gao arXiv preprint arXiv:2304.13826, 2023 | 32 | 2023 |
| Program-guided image manipulators J Mao, X Zhang, Y Li, WT Freeman, JB Tenenbaum, J Wu Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 23 | 2019 |
| Translating a visual lego manual to a machine-executable plan R Wang, Y Zhang, J Mao, CY Cheng, J Wu European Conference on Computer Vision, 677-694, 2022 | 21 | 2022 |
| FALCON: fast visual concept learning by integrating images, linguistic descriptions, and conceptual relations L Mei, J Mao, Z Wang, C Gan, JB Tenenbaum arXiv preprint arXiv:2203.16639, 2022 | 20 | 2022 |
| Object-centric diagnosis of visual reasoning J Yang, J Mao, J Wu, D Parikh, DD Cox, JB Tenenbaum, C Gan arXiv preprint arXiv:2012.11587, 2020 | 18 | 2020 |
| Compositional diffusion-based continuous constraint solvers Z Yang, J Mao, Y Du, J Wu, JB Tenenbaum, T Lozano-Pérez, ... arXiv preprint arXiv:2309.00966, 2023 | 17 | 2023 |
| CLEVRER-Humans: Describing physical and causal events the human way J Mao, X Yang, X Zhang, N Goodman, J Wu Advances in Neural Information Processing Systems 35, 7755-7768, 2022 | 17 | 2022 |
| Learning Adaptive Planning Representations with Natural Language Guidance L Wong, J Mao, P Sharma, ZS Siegel, J Feng, N Korneev, JB Tenenbaum, ... arXiv preprint arXiv:2312.08566, 2023 | 15 | 2023 |
Joshua B. TenenbaumMITVerified email at mit.edu
