[44] Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dólar, and C Lawrence Zitnick. Microsoft coco: Common objects in context. In ECCV, 2014. 3, 6, 10
[45] Huanyu Liu, Chao Peng, Changqian Yu, Jingbo Wang, Xu Liu, Gang Yu, and Wei Jiang. An end-to-end network for panoptic segmentation. In CVPR, 2019. 3
[46] Ze Liu, Yutong Lin, Yue Cao, Han Hu, Yixuan Wei, Zheng Zhang, Stephen Lin, and Baining Guo. Swin transformer: Hierarchical vision transformer using shifted windows. In ICCV, 2021. 10, 16
[47] Zhuang Liu, Hanzi Mao, Chao-Yuan Wu, Christoph Feichtenhofer, Trevor Darrell, and Saining Xie. A convnet for the 2020s. In CVPR, 2022. 3, 10
[48] Jonathan Long, Evan Shelhamer, and Trevor Darrell. Fully convolutional networks for semantic segmentation. In CVPR, 2015. 3
[49] Ilya Loshchilov and Frank Hutter. Decoupled weight decay regularization. In ICLR, 2019. 7
[50] Depu Meng, Xiaokang Chen, Zejia Fan, Gang Zeng, Houqiang Li, Yuhui Yuan, Lei Sun, and Jingdong Wang. Conditional detr for fast training convergence. In ICCV, 2021. 3
[51] Rohit Mohan and Abhinav Valada. Efficients: Efficient panoptic segmentation. IJCV, 129(5):1551-1579, 2021. 3
[52] Gerhard Neuhold, Tobias Ollmann, Samuel Rota Bulo, and Peter Kontschieder. The mapillary vistas dataset for semantic understanding of street scenes. In ICCV, 2017. 10
[53] Lorenzo Porzi, Samuel Rota Bulò, Aleksander Colovic, and Peter Kontschieder. Seamless scene segmentation. In CVPR, 2019. 1, 3
[54] Siyuan Qiao, Liang-Chieh Chen, and Alan Yuille. Detectors: Detecting objects with recursive feature pyramid and switchable atrous convolution. In CVPR, 2021. 3
[55] Abdullah Rashwan, Yeqing Li, Xingyi Zhou, Jiageng Zhang, and Fan Yang. Maskconver: A universal panoptic and semantic segmentation model with pure convolutions. OpenReview, 2023. 3, 6, 7
[56] Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael S. Bernstein, Alexander C. Berg, and Li Fei-Fei. Imagenet large scale visual recognition challenge. IJCV, 115:211–252, 2015. 4, 7
[57] Mark Sandler, Andrew Howard, Menglong Zhu, Andrey Zhmoginov, and Liang-Chieh Chen. Mobilenetv2: Inverted residuals and linear bottlenecks. In CVPR, 2018. 1
[58] Inkyu Shin, Dahun Kim, Qihang Yu, Jun Xie, Hong-Seok Kim, Bradley Green, In So Kweon, Kuk-Jin Yoon, and Liang-Chieh Chen. Video-kmax: A simple unified approach for online and near-online video panoptic segmentation. In WACV, 2024. 7
[59] Robin Strudel, Ricardo Garcia, Ivan Laptev, and Cordelia Schmid. Segmenter: Transformer for semantic segmentation. In ICCV, 2021. 3
[60] Shuyang Sun, Jie-Neng Chen, Ruifei He, Alan Yuille, Philip Torr, and Song Bai. Lumix: Improving mixup by better modelling label uncertainty. arXiv preprint arXiv:2211.15846, 2022. 4
[61] Christian Szegedy, Vincent Vanhoucke, Sergey Ioffe, Jon Shlens, and Zbigniew Wojna. Rethinking the inception architecture for computer vision. In CVPR, 2016. 4
[62] Zhi Tian, Chunhua Shen, and Hao Chen. Conditional convolutions for instance segmentation. In ECCV, 2020.3
[63] Zhuowen Tu, Xiangrong Chen, Alan L Yuille, and Song-Chun Zhu. Image parsing: Unifying segmentation, detection, and recognition. IJCV, 63:113-140, 2005. 1
[64] Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Lukasz Kaiser, and Illia Polosukhin. Attention is all you need. NeurIPS, 2017. 1, 3, 4
[65] Huiyu Wang, Yukun Zhu, Bradley Green, Hartwig Adam, Alan Yuille, and Liang-Chieh Chen. Axial-DeepLab: Stand-Alone Axial-Attention for Panoptic Segmentation. In ECCV, 2020. 3, 16
[66] Huiyu Wang, Yukun Zhu, Hartwig Adam, Alan Yuille, and Liang-Chieh Chen. Max-deeplab: End-to-end panoptic segmentation with mask transformers. In CVPR, 2021. 1, 2, 3, 4, 6, 7, 10, 16