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Recently Transformer has been largely explored in tracking and shown state-of-the-art (SOTA) performance.
Imagenet classification with deep convolutional neural networks
Krizhevsky, A., Sutskever, I., Hinton, G.E., 2012 · 2012
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Microsoft coco: Common objects in context, in: ECCV
Lin, T.Y., Maire, M., Belongie, S., Hays, J., Perona, P., Ramanan, D., Dollár, P., Zitnick, C.L., 2014 · 2014
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Faster r-cnn: Towards real-time object detection with region proposal networks, in: NIPS
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Fully-convolutional siamese networks for object tracking, in: ECCVW
Bertinetto, L., Valmadre, J., Henriques, J.F., Vedaldi, A., Torr, P.H., 2016 · 2016
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Deep residual learning for image recognition, in: CVPR
He, K., Zhang, X., Ren, S., Sun, J., 2016 · 2016
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A novel performance evaluation methodology for single-target trackers
Kristan, M., Matas, J., Leonardis, A., Vojir, T., Pflugfelder, R., Fernandez, G., Nebehay, G., Porikli, F., Čehovin, L., 2016 · 2016
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Fractalnet: Ultra-deep neural networks without residuals, in: ICLR
Larsson, G., Maire, M., Shakhnarovich, G., 2016 · 2016
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A benchmark and simulator for uav tracking, in: ECCV
Mueller, M., Smith, N., Ghanem, B., 2016 · 2016
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Attention is all you need, in: NeurIPS
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, Ł., Polosukhin, I., 2017 · 2017
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High performance visual tracking with siamese region proposal network, in: CVPR
Li, B., Yan, J., Wu, W., Zhu, Z., Hu, X., 2018 · 2018
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Trackingnet: A large-scale dataset and benchmark for object tracking in the wild, in: ECCV
Muller, M., Bibi, A., Giancola, S., Alsubaihi, S., Ghanem, B., 2018 · 2018
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Self-attention with relative position representations
Shaw, P., Uszkoreit, J., Vaswani, A., 2018 · 2018
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Learning discriminative model prediction for tracking, in: ICCV
Bhat, G., Danelljan, M., Gool, L.V., Timofte, R., 2019 · 2019
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Atom: Accurate tracking by overlap maximization, in: CVPR
Danelljan, M., Bhat, G., Khan, F.S., Felsberg, M., 2019 · 2019
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Lasot: A high-quality benchmark for large-scale single object tracking, in: CVPR
Fan, H., Lin, L., Yang, F., Chu, P., Deng, G., Yu, S., Bai, H., Xu, Y., Liao, C., Ling, H., 2019 · 2019
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Siamese cascaded region proposal networks for real-time visual tracking, in: CVPR
Fan, H., Ling, H., 2019 · 2019
Cited alongside, same era.
Got-10k: A large high-diversity benchmark for generic object tracking in the wild
Huang, L., Zhao, X., Huang, K., 2019 · 2019
Cited alongside, same era.
Evolution of siamese visual tracking with very deep networks, in: CVPR
Li, B., Wu, W., Wang, Q., Zhang, F., Xing, J., Yan, J.S., 2019 · 2019
Cited alongside, same era.
Decoupled weight decay regularization, in: ICLR
Loshchilov, I., Hutter, F., 2019 · 2019
Cited alongside, same era.
Generalized intersection over union
Rezatofighi, H., Tsoi, N., Gwak, J., Sadeghian, A., Reid, I., Savarese, S., 2019 · 2019
Cited alongside, same era.
End-to-end object detection with transformers, in: ECCV
Carion, N., Massa, F., Synnaeve, G., Usunier, N., Kirillov, A., Zagoruyko, S., 2020 · 2020
Stmtrack: Template-free visual tracking with space-time memory networks, in: CVPR
Fu, Z., Liu, Q., Fu, Z., Wang, Y., 2021 · 2021
Closest in time.
Learning to fuse asymmetric feature maps in siamese trackers, in: CVPR
Han, W., Dong, X., Khan, F.S., Shao, L., Shen, J., 2021 · 2021
Closest in time.
Rethinking positional encoding in language pre-training, in: ICLR
Ke, G., He, D., Liu, T.Y., 2021 · 2021
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Swin transformer: Hierarchical vision transformer using shifted windows
Liu, Z., Lin, Y., Cao, Y., Hu, H., Wei, Y., Zhang, Z., Lin, S., Guo, B., 2021 · 2021
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Learning target candidate association to keep track of what not to track, in: ICCV
Mayer, C., Danelljan, M., Paudel, D.P., Van Gool, L., 2021 · 2021
Closest in time.
Training data-efficient image transformers & distillation through attention, in: ICML
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Cited alongside, same era.
High-performance long-term tracking with meta-updater, in: CVPR
Dai, K., Zhang, Y., Wang, D., Li, J., Lu, H., Yang, X., 2020 · 2020
Cited alongside, same era.
Generalized focal loss: Learning qualified and distributed bounding boxes for dense object detection, in: NeurIPS
Li, X., Wang, W., Wu, L., Chen, S., Hu, X., Li, J., Tang, J., Yang, J., 2020 · 2020
Cited alongside, same era.
Siam r-cnn: Visual tracking by re-detection, in: CVPR
Voigtlaender, P., Luiten, J., Torr, P.H., Leibe, B., 2020 · 2020
Cited alongside, same era.
Siamfc++: Towards robust and accurate visual tracking with target estimation guidelines, in: AAAI
Xu, Y., Wang, Z., Li, Z., Yuan, Y., Yu, G., 2020 · 2020
Cited alongside, same era.
Deformable siamese attention networks for visual object tracking, in: CVPR
Yu, Y., Xiong, Y., Huang, W., Scott, M.R., 2020 · 2020
Cited alongside, same era.
Ocean: Object-aware anchor-free tracking, in: ECCV
Zhang, Z., Peng, H., Fu, J., Li, B., Hu, W., 2020 · 2020
Cited alongside, same era.
Touvron, H., Cord, M., Douze, M., Massa, F., Sablayrolles, A., Jégou, H., 2021 · 2021
Closest in time.
Learning spatio-temporal transformer for visual tracking, in: ICCV
Yan, B., Peng, H., Fu, J., Wang, D., Lu, H., 2021 · 2021
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Tokens-to-token vit: Training vision transformers from scratch on imagenet, in: ICCV
Yuan, L., Chen, Y., Wang, T., Yu, W., Shi, Y., Jiang, Z.H., Tay, F.E., Feng, J., Yan, S., 2021 · 2021
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Mixformer: End-to-end tracking with iterative mixed attention, in: CVPR
Cui, Y., Jiang, C., Wang, L., Wu, G., 2022 · 2022
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Aiatrack: Attention in attention for transformer visual tracking
Gao, S., Zhou, C., Ma, C., Wang, X., Yuan, J., 2022 · 2022
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Masked autoencoders are scalable vision learners, in: CVPR
He, K., Chen, X., Xie, S., Li, Y., Dollár, P., Girshick, R., 2022 · 2022
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Transforming model prediction for tracking, in: CVPR
Mayer, C., Danelljan, M., Bhat, G., Paul, M., Paudel, D.P., Yu, F., Van Gool, L., 2022 · 2022
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Correlation-aware deep tracking, in: CVPR
Xie, F., Wang, C., Wang, G., Cao, Y., Yang, W., Zeng, W., 2022 · 2022
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Towards grand unification of object tracking, in: ECCV
Yan, B., Jiang, Y., Sun, P., Wang, D., Yuan, Z., Luo, P., Lu, H., 2022 · 2022
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Joint feature learning and relation modeling for tracking: A one-stream framework
Ye, B., Chang, H., Ma, B., Shan, S., Chen, X., 2022 · 2022
Closest in time.