The Overlooked Classifier in Human-Object Interaction Recognition

Maron, O., Lozano-Pérez, T.: A framework for multiple-instance learning. Advances in neural information processing systems pp. 570–576 (1998)

1998

Earlier work this paper cites.

Glorot, X., Bengio, Y.: Understanding the difficulty of training deep feedforward neural networks. In: Proceedings of the thirteenth international conference on artificial intelligence and statistics. pp. 249–256. JMLR Workshop and Conference Proceedings (2010)

2010

Earlier work this paper cites.

Ordonez, V., Kulkarni, G., Berg, T.: Im2text: Describing images using 1 million captioned photographs. Advances in neural information processing systems 24

2011

Earlier work this paper cites.

Andriluka, M., Pishchulin, L., Gehler, P., Schiele, B.: 2d human pose estimation: New benchmark and state of the art analysis. In: Proceedings of the IEEE Conference on computer Vision and Pattern Recognition. pp. 3686–3693 (2014)

2014

Earlier work this paper cites.

Kingma, D.P., Ba, J.: Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980 (2014)

Original

2014

Earlier work this paper cites.

Lin, T.Y., Maire, M., Belongie, S., Hays, J., Perona, P., Ramanan, D., Dollár, P., Zitnick, C.L.: Microsoft coco: Common objects in context. In: European conference on computer vision. pp. 740–755. Springer (2014)

2014

Earlier work this paper cites.

Chao, Y.W., Wang, Z., He, Y., Wang, J., Deng, J.: Hico: A benchmark for recognizing human-object interactions in images. In: Proceedings of the IEEE International Conference on Computer Vision. pp. 1017–1025 (2015)

2015

Earlier work this paper cites.

Gkioxari, G., Girshick, R., Malik, J.: Contextual action recognition with r* cnn. In: Proceedings of the IEEE international conference on computer vision. pp. 1080–1088 (2015)

2015

Earlier work this paper cites.

He, K., Zhang, X., Ren, S., Sun, J.: Delving deep into rectifiers: Surpassing human-level performance on imagenet classification. In: Proceedings of the IEEE international conference on computer vision. pp. 1026–1034 (2015)

2015

Earlier work this paper cites.

Mostajabi, M., Yadollahpour, P., Shakhnarovich, G.: Feedforward semantic segmentation with zoom-out features. In: Proceedings of the IEEE conference on computer vision and pattern recognition. pp. 3376–3385 (2015)

2015

Earlier work this paper cites.

He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: Proceedings of the IEEE conference on computer vision and pattern recognition. pp. 770–778 (2016)

2016

Earlier work this paper cites.

Loshchilov, I., Hutter, F.: Sgdr: Stochastic gradient descent with warm restarts. arXiv preprint arXiv:1608.03983 (2016)

Original

2016

Earlier work this paper cites.

Mallya, A., Lazebnik, S.: Learning models for actions and person-object interactions with transfer to question answering. In: European Conference on Computer Vision. pp. 414–428. Springer (2016)

2016

Earlier work this paper cites.

Girdhar, R., Ramanan, D.: Attentional pooling for action recognition. In: Proceedings of the 31st International Conference on Neural Information Processing Systems. pp. 33–44 (2017)

2017

Earlier work this paper cites.

Krishna, R., Zhu, Y., Groth, O., Johnson, J., Hata, K., Kravitz, J., Chen, S., Kalantidis, Y., Li, L.J., Shamma, D.A., et al.: Visual genome: Connecting language and vision using crowdsourced dense image annotations. International journal of computer vision 123

2017

Earlier work this paper cites.

Lin, T.Y., Goyal, P., Girshick, R., He, K., Dollár, P.: Focal loss for dense object detection. In: Proceedings of the IEEE international conference on computer vision. pp. 2980–2988 (2017)

2017

Earlier work this paper cites.

Wang, F., Xiang, X., Cheng, J., Yuille, A.L.: Normface: L2 hypersphere embedding for face verification. In: Proceedings of the 25th ACM international conference on Multimedia. pp. 1041–1049 (2017)

2017

Earlier work this paper cites.

Xu, D., Zhu, Y., Choy, C.B., Fei-Fei, L.: Scene graph generation by iterative message passing. In: Proceedings of the IEEE conference on computer vision and pattern recognition. pp. 5410–5419 (2017)

2017

Earlier work this paper cites.

Chao, Y.W., Liu, Y., Liu, X., Zeng, H., Deng, J.: Learning to detect human-object interactions. In: 2018 ieee winter conference on applications of computer vision (wacv). pp. 381–389. IEEE (2018)

2018

Cited alongside, same era.

Devlin, J., Chang, M.W., Lee, K., Toutanova, K.: Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805 (2018)

Original

2018

Cited alongside, same era.

Fang, H.S., Cao, J., Tai, Y.W., Lu, C.: Pairwise body-part attention for recognizing human-object interactions. In: Proceedings of the European conference on computer vision (ECCV). pp. 51–67 (2018)

2018

Cited alongside, same era.

Gao, C., Zou, Y., Huang, J.B.: ican: Instance-centric attention network for human-object interaction detection. arXiv preprint arXiv:1808.10437 (2018)

Original

2018

Cited alongside, same era.

Liao, Y., Liu, S., Wang, F., Chen, Y., Qian, C., Feng, J.: Ppdm: Parallel point detection and matching for real-time human-object interaction detection. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 482–490 (2020)

2020

Later among the works it cites.

Liu, Y., Chen, Q., Zisserman, A.: Amplifying key cues for human-object-interaction detection. In: European Conference on Computer Vision. pp. 248–265. Springer (2020)

2020

Later among the works it cites.

Sun, Y., Cheng, C., Zhang, Y., Zhang, C., Zheng, L., Wang, Z., Wei, Y.: Circle loss: A unified perspective of pair similarity optimization. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 6398–6407 (2020)

2020

Later among the works it cites.

Wang, T., Yang, T., Danelljan, M., Khan, F.S., Zhang, X., Sun, J.: Learning human-object interaction detection using interaction points. In: CVPR (2020)

2020

Later among the works it cites.