| Visual question answering: Datasets, algorithms, and future challenges K Kafle, C Kanan Computer Vision and Image Understanding 163, 3-20, 2017 | 203 | 2017 |
| An analysis of visual question answering algorithms K Kafle, C Kanan Proceedings of the IEEE international conference on computer vision, 1965-1973, 2017 | 203 | 2017 |
| Remind your neural network to prevent catastrophic forgetting TL Hayes, K Kafle, R Shrestha, M Acharya, C Kanan Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 175 | 2020 |
| Dvqa: Understanding data visualizations via question answering K Kafle, B Price, S Cohen, C Kanan Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 154 | 2018 |
| Answer-type prediction for visual question answering K Kafle, C Kanan Proceedings of the IEEE conference on computer vision and pattern …, 2016 | 141 | 2016 |
| Data augmentation for visual question answering K Kafle, M Yousefhussien, C Kanan Proceedings of the 10th International Conference on Natural Language …, 2017 | 119 | 2017 |
| On the value of out-of-distribution testing: An example of goodhart's law D Teney, E Abbasnejad, K Kafle, R Shrestha, C Kanan, ... Advances in Neural Information Processing Systems 33, 407-417, 2020 | 90 | 2020 |
| Answer them all! toward universal visual question answering models R Shrestha, K Kafle, C Kanan Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 82 | 2019 |
| TallyQA: Answering complex counting questions M Acharya, K Kafle, C Kanan Proceedings of the AAAI conference on artificial intelligence 33 (01), 8076-8084, 2019 | 42 | 2019 |
| Answering questions about data visualizations using efficient bimodal fusion K Kafle, R Shrestha, S Cohen, B Price, C Kanan Proceedings of the IEEE/CVF Winter conference on applications of computer …, 2020 | 38 | 2020 |
| A negative case analysis of visual grounding methods for vqa R Shrestha, K Kafle, C Kanan arXiv preprint arXiv:2004.05704, 2020 | 37 | 2020 |
| Learning to predict visual attributes in the wild K Pham, K Kafle, Z Lin, Z Ding, S Cohen, Q Tran, A Shrivastava Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 36 | 2021 |
| Challenges and prospects in vision and language research K Kafle, R Shrestha, C Kanan Frontiers in Artificial Intelligence 2, 28, 2019 | 32 | 2019 |
| An investigation of critical issues in bias mitigation techniques R Shrestha, K Kafle, C Kanan Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2022 | 18 | 2022 |
| Question answering for data visualizations S Cohen, K Kafle, B Price US Patent 10,754,851, 2020 | 12 | 2020 |
| Do we need fully connected output layers in convolutional networks? Z Qian, TL Hayes, K Kafle, C Kanan arXiv preprint arXiv:2004.13587, 2020 | 7 | 2020 |
| Occamnets: Mitigating dataset bias by favoring simpler hypotheses R Shrestha, K Kafle, C Kanan Computer Vision–ECCV 2022: 17th European Conference, Tel Aviv, Israel …, 2022 | 4 | 2022 |
| AESOP: Abstract Encoding of Stories, Objects, and Pictures H Ravi, K Kafle, S Cohen, J Brandt, M Kapadia Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 3 | 2021 |
| A Bayesian model of visual question answering C Kanan, K Kafle Journal of Vision 16 (12), 332-332, 2016 | 3 | 2016 |
| Improving Closed and Open-Vocabulary Attribute Prediction Using Transformers K Pham, K Kafle, Z Lin, Z Ding, S Cohen, Q Tran, A Shrivastava Computer Vision–ECCV 2022: 17th European Conference, Tel Aviv, Israel …, 2022 | 2 | 2022 |
Christopher KananUniversity of Rochester在 cs.rochester.edu 的電子郵件地址已通過驗證
