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PreviewIssue DateTitleAuthor(s)
2017The VQA-machine: learning how to use existing vision algorithms to answer new questionsWang, P.; Wu, Q.; Shen, C.; van den Hengel, A.; 30th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2017) (21 Jul 2017 - 26 Jul 2017 : Honolulu)
2019V-PROM: A Benchmark for Visual Reasoning Using Visual Progressive Matrices.Teney, D.; Wang, P.; Cao, J.; Liu, L.; Shen, C.; Hengel, A.V.D.; 34th AAAI Conference on Artificial Intelligence / 32nd Innovative Applications of Artificial Intelligence Conference / 10th AAAI Symposium on Educational Advances in Artificial Intelligence (7 Feb 2020 - 12 Feb 2020 : New York, NY)
2017Explicit knowledge-based reasoning for visual question answeringWang, P.; Wu, Q.; Shen, C.; Dick, A.; Van Den Hengel, A.; Sierra, C.; 26th International Joint Conference on Artificial Intelligence (IJCAI-17) (19 Aug 2017 - 26 Aug 2017 : Melbourne)
2020Adaptive importance learning for improving lightweight image super-resolution networkZhang, L.; Wang, P.; Shen, C.; Liu, L.; Wei, W.; Zhang, Y.; van den Hengel, A.
2019Visual question answering as reading comprehensionLi, H.; Wang, P.; Shen, C.; Van Den Hengel, A.; IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (15 Jun 2019 - 20 Jun 2019 : Long Beach, USA)
2019Unsupervised domain adaptation using robust class-wise matchingZhang, L.; Wang, P.; Wei, W.; Lu, H.; Shen, C.; van den Hengel, A.; Zhang, Y.
2018Pushing the limits of deep CNNs for pedestrian detectionHu, Q.; Wang, P.; Shen, C.; Van Den Hengel, A.; Porikli, F.
2017FVQA: fact-based Visual Question AnsweringWang, P.; Wu, Q.; Shen, C.; Dick, A.; Van Den Hengel, A.