A Lightweight Transformer-Based Model for Fight Recognition
Tác giả
Tóm tắt
Tài liệu tham khảo
[1] Bermejo Nievas, E., Deniz Suarez, O., Bueno García, G., Sukthankar, R.: Violence detection in video using computer vision techniques. In: Real, P., Diaz-Pernil, D., Molina-Abril, H., Berciano, A., Kropatsch, W. (eds.) CAIP 2011. LNCS, vol. 6855, pp. 332–339. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-23678-5_39
[2] Carneiro, S.A., da Silva, G.P., Guimaraes, S.J.F., Pedrini, H.: Fight detection in video sequences based on multi-stream convolutional neural networks. In: SIBGRAPI, pp. 8–15. IEEE (2019)
[3] Chen, Y., et al.: Mobile-former: Bridging mobilenet and transformer. In: CVPR, pp. 5270–5279 (2022)
[4] Cheng, M., Cai, K., Li, M.: RWF-2000: an open large scale video database for violence detection. In: ICPR, pp. 4183–4190 (2021)
[5] Cheng, W.C., Mai, T.H., Lin, H.T.: From SMOTE to mixup for deep imbalanced classification. In: Lee, C.Y., Lin, C.L., Chang, H.T. (eds.) TAAI 2023. CCIS, vol. 2074, pp. 75–96. Springer, Cham (2023)
[6] Cubuk, E.D., Zoph, B., Shlens, J., Le, Q.V.: RandAugment: practical automated data augmentation with a reduced search space. In: CVPR, pp. 702–703 (2020)
[7] Dang, A., Linh, H.M., Vu, D.Q.: Multi-scale aggregation network for speech emotion recognition. In: Hà, M.H., Zhu, X., Thai, M.T. (eds.) CSoNet. LNCS, vol. 14479, pp. 63–73. Springer, Singapore (2023). https://doi.org/10.1007/978-981-97-0669-3_6
[8] Feichtenhofer, C., Fan, H., Malik, J., He, K.: Slowfast networks for video recognition. In: ICCV, pp. 6202–6211 (2019)
[9] He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: CVPR, pp. 770–778 (2016)
[10] Howard, A., et al.: Searching for mobilenetv3. In: ICCV, pp. 1314–1324 (2019)
[11] Kang, M.S., Park, R.H., Park, H.M.: Efficient spatio-temporal modeling methods for real-time violence recognition. IEEE Access 9, 76270–76285 (2021)
[12] Khan, M., El Saddik, A., Gueaieb, W., De Masi, G., Karray, F.: VD-Net: an edge vision-based surveillance system for violence detection. IEEE Access 12 (2024)
[13] Nga, C.H., Vu, D.Q., Luong, H.H., Huang, C.L., Wang, J.C.: Cyclic transfer learning for mandarin-english code-switching speech recognition. IEEE Signal Process. Lett. (2023)
[14] Phung, T., Nguyen, V.T., Ma, T.H.T., Duc, Q.V.: A (2+1) d attention convolutional neural network for video prediction. In: Dang, N.H.T., Zhang, YD., Tavares, J.M.R.S., Chen, BH. (eds.) ICABDE 2021, vol. 124, pp. 395–406. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-97610-1_31
[15] Serrano Gracia, I., Deniz Suarez, O., Bueno Garcia, G., Kim, T.K.: Fast fight detection. PloS one 10(4), e0120448 (2015)
[16] Soliman, M.M., Kamal, M.H., Nashed, M.A.E.M., Mostafa, Y.M., Chawky, B.S., Khattab, D.: Violence recognition from videos using deep learning techniques. In: ICICIS, pp. 80–85. IEEE (2019)
[17] Sudhakaran, S., Lanz, O.: Learning to detect violent videos using convolutional long short-term memory. In: AVSS, pp. 1–6. IEEE (2017)
[18] Tan, H.M., Vu, D.Q., Thi, D.N., Thu, T.P.T.: Voice separation using multi learning on squash-norm embedding matrix and mask. In: Nghia, P.T., Thai, V.D., Thuy, N.T., Son, L.H., Huynh, V.N. (eds.) ICTA 2023. LNNS, vol. 848, pp. 327–333. Springer, Cham (2023). https://doi.org/10.1007/978-3-031-50818-9_36
[19] Tan, H.M., Vu, D.Q., Wang, J.C.: Selinet: a lightweight model for single channel speech separation. In: ICASSP, pp. 1–5. IEEE (2023)
[20] Tan, M., Le, Q.: EfficientNet: rethinking model scaling for convolutional neural networks. In: ICML, pp. 6105–6114. PMLR (2019)
[21] Tran, D., et al.: A closer look at spatiotemporal convolutions for action recognition. In: CVPR, pp. 6450–6459 (2018)
[22] Tran, H.N., Jeon, J.W.: Robust speed controller using dual adaptive sliding mode control (DA-SMC) method for PMSM drives. IEEE Access 11, 63261–63270 (2023)
[23] Vaswani, A., et al.: Attention is all you need. NIPS 30 (2017)
[24] Vu, D.Q., Nguyen, T.H., Nguyen, M., Nguyen, B.Y., Phung, T.N., Thu, T.P.T.: TNUE-Fight detection: a new challenge benchmark for fighting recognition. In: Nghia, P.T., Thai, V.D., Thuy, N.T., Son, L.H., Huynh, V.N. (eds.) ICTA 2023. LNNS, vol. 848, pp. 308–314. Springer, Cham (2023)
[25] Vu, D.Q., Phung, T.T., Wang, J.C., Mai, S.T.: LCSL: long-tailed classification via self-labeling. IEEE TCSVT (2024)
[26] Vu, D.Q., Thu, T.P.T.: Simultaneous context and motion learning in video prediction. SIViP 17(8), 3933–3942 (2023)
[27] Wang, J., Zhao, D., Li, H., Wang, D.: Lightweight violence detection model based on 2D CNN with bi-directional motion attention. Appl. Sci. 14(11) (2024)