Scene parsing through ADE20k dataset. Scene parsing, or recognizing and segmenting objects and stuff in an image, is one of the key problems in computer vision. Despite the communitys efforts in data collection, there are still few image datasets covering a wide range of scenes and object categories with dense and detailed annotations for scene parsing. In this paper, we introduce and analyze the ADE20K dataset, spanning diverse annotations of scenes, objects, parts of objects, and in some cases even parts of parts. A scene parsing benchmark is built upon the ADE20K with 150 object and stuff classes included. Several segmentation baseline models are evaluated on the benchmark. A novel network design called Cascade Segmentation Module is proposed to parse a scene into stuff, objects, and object parts in a cascade and improve over the baselines. We further show that the trained scene parsing networks can lead to applications such as image content removal and scene synthesis

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  1. Marcos Nieto, Orti Senderos, Oihana Otaegui: Boosting AI applications: Labeling format for complex datasets (2021) not zbMATH
  2. Mark Weber, Huiyu Wang, Siyuan Qiao, Jun Xie, Maxwell D. Collins, Yukun Zhu, Liangzhe Yuan, Dahun Kim, Qihang Yu, Daniel Cremers, Laura Leal-Taixe, Alan L. Yuille, Florian Schroff, Hartwig Adam, Liang-Chieh Chen: DeepLab2: A TensorFlow Library for Deep Labeling (2021) arXiv
  3. Qi, Zhongang; Khorram, Saeed; Fuxin, Li: Embedding deep networks into visual explanations (2021)
  4. Yuan, Yuhui; Huang, Lang; Guo, Jianyuan; Zhang, Chao; Chen, Xilin; Wang, Jingdong: OCNet: object context for semantic segmentation (2021)
  5. Shao, Wenqi; Li, Jingyu; Ren, Jiamin; Zhang, Ruimao; Wang, Xiaogang; Luo, Ping: SSN: learning sparse switchable normalization via SparsestMax (2020)
  6. Wang, Xiang; Liu, Sifei; Ma, Huimin; Yang, Ming-Hsuan: Weakly-supervised semantic segmentation by iterative affinity learning (2020)
  7. Wang, Yong; Zhang, Dongfang; Dai, Guangming: Classification of high resolution satellite images using improved U-Net (2020)
  8. Pei Sun, Henrik Kretzschmar, Xerxes Dotiwalla, Aurelien Chouard, Vijaysai Patnaik, Paul Tsui, James Guo, Yin Zhou, Yuning Chai, Benjamin Caine, Vijay Vasudevan, Wei Han, Jiquan Ngiam, Hang Zhao, Aleksei Timofeev, Scott Ettinger, Maxim Krivokon, Amy Gao, Aditya Joshi, Sheng Zhao, Shuyang Cheng, Yu Zhang, Jonathon Shlens, Zhifeng Chen, Dragomir Anguelov: Scalability in Perception for Autonomous Driving: Waymo Open Dataset (2019) arXiv