{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,21]],"date-time":"2025-12-21T10:03:42Z","timestamp":1766311422391,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":33,"publisher":"ACM","license":[{"start":{"date-parts":[[2019,10,15]],"date-time":"2019-10-15T00:00:00Z","timestamp":1571097600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/501100012659","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61807033"],"award-info":[{"award-number":["61807033"]}],"id":[{"id":"10.13039\/501100012659","id-type":"DOI","asserted-by":"publisher"}]},{"name":"US Natural Science Foundation","award":["IIS1816227"],"award-info":[{"award-number":["IIS1816227"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2019,10,15]]},"DOI":"10.1145\/3343031.3350989","type":"proceedings-article","created":{"date-parts":[[2019,10,21]],"date-time":"2019-10-21T16:32:26Z","timestamp":1571675546000},"page":"2152-2160","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":24,"title":["Data Priming Network for Automatic Check-Out"],"prefix":"10.1145","author":[{"given":"Congcong","family":"Li","sequence":"first","affiliation":[{"name":"University of Chinese Academy of Sciences, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dawei","family":"Du","sequence":"additional","affiliation":[{"name":"University at Albany, State University of New York, Albany, NY, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Libo","family":"Zhang","sequence":"additional","affiliation":[{"name":"Institute of Software Chinese Academy of Sciences &amp; State Key Laboratory of Computer Science, ISCAS, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tiejian","family":"Luo","sequence":"additional","affiliation":[{"name":"University of Chinese Academy of Sciences, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yanjun","family":"Wu","sequence":"additional","affiliation":[{"name":"Institute of Software Chinese Academy of Sciences &amp; State Key Laboratory of Computer Science, ISCAS, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qi","family":"Tian","sequence":"additional","affiliation":[{"name":"Huawei Noah's Ark Lab, Shenzhen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Longyin","family":"Wen","sequence":"additional","affiliation":[{"name":"JD Digits, Mountain View, CA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Siwei","family":"Lyu","sequence":"additional","affiliation":[{"name":"University at Albany, State University of New York, Albany, NY, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2019,10,15]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"crossref","unstructured":"Yuhua Chen Wen Li Christos Sakaridis Dengxin Dai and Luc Van Gool. 2018. Domain Adaptive Faster R-CNN for Object Detection in the Wild. In CVPR . 3339--3348.  Yuhua Chen Wen Li Christos Sakaridis Dengxin Dai and Luc Van Gool. 2018. Domain Adaptive Faster R-CNN for Object Detection in the Wild. In CVPR . 3339--3348.","DOI":"10.1109\/CVPR.2018.00352"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"crossref","unstructured":"Piotr Doll\u00e1 r and C. Lawrence Zitnick. 2013. Structured Forests for Fast Edge Detection. In ICCV. 1841--1848.  Piotr Doll\u00e1 r and C. Lawrence Zitnick. 2013. Structured Forests for Fast Edge Detection. In ICCV. 1841--1848.","DOI":"10.1109\/ICCV.2013.231"},{"key":"e_1_3_2_1_3_1","volume-title":"Philipp H\"a rtinger, Rebecca K\u00f6 nig, and Markus Ulrich.","author":"Follmann Patrick","year":"2018","unstructured":"Patrick Follmann , Tobias B\u00f6 ttger , Philipp H\"a rtinger, Rebecca K\u00f6 nig, and Markus Ulrich. 2018 . MVTec D2S: Densely Segmented Supermarket Dataset. In ECCV. 581--597. Patrick Follmann, Tobias B\u00f6 ttger, Philipp H\"a rtinger, Rebecca K\u00f6 nig, and Markus Ulrich. 2018. MVTec D2S: Densely Segmented Supermarket Dataset. In ECCV. 581--597."},{"key":"e_1_3_2_1_4_1","volume-title":"Lempitsky","author":"Ganin Yaroslav","year":"2015","unstructured":"Yaroslav Ganin and Victor S . Lempitsky . 2015 . Unsupervised Domain Adaptation by Backpropagation. In ICML. 1180--1189. Yaroslav Ganin and Victor S. Lempitsky. 2015. Unsupervised Domain Adaptation by Backpropagation. In ICML. 1180--1189."},{"key":"e_1_3_2_1_5_1","volume-title":"Recognizing Products: A Per-exemplar Multi-label Image Classification Approach. In ECCV . 440--455.","author":"George Marian","year":"2014","unstructured":"Marian George and Christian Floerkemeier . 2014 . Recognizing Products: A Per-exemplar Multi-label Image Classification Approach. In ECCV . 440--455. Marian George and Christian Floerkemeier. 2014. Recognizing Products: A Per-exemplar Multi-label Image Classification Approach. In ECCV . 440--455."},{"key":"e_1_3_2_1_6_1","unstructured":"Ian J. Goodfellow Jean Pouget-Abadie Mehdi Mirza Bing Xu David Warde-Farley Sherjil Ozair Aaron C. Courville and Yoshua Bengio. 2014. Generative Adversarial Nets. In NeurIPS. 2672--2680.  Ian J. Goodfellow Jean Pouget-Abadie Mehdi Mirza Bing Xu David Warde-Farley Sherjil Ozair Aaron C. Courville and Yoshua Bengio. 2014. Generative Adversarial Nets. In NeurIPS. 2672--2680."},{"key":"e_1_3_2_1_7_1","unstructured":"Kaiming He Xiangyu Zhang Shaoqing Ren and Jian Sun. 2016. Deep Residual Learning for Image Recognition. In CVPR. 770--778.  Kaiming He Xiangyu Zhang Shaoqing Ren and Jian Sun. 2016. Deep Residual Learning for Image Recognition. In CVPR. 770--778."},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2018.2815688"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2016.2594489"},{"key":"e_1_3_2_1_10_1","volume-title":"The Freiburg Groceries Dataset. CoRR","author":"Jund Philipp","year":"2016","unstructured":"Philipp Jund , Nichola Abdo , Andreas Eitel , and Wolfram Burgard . 2016. The Freiburg Groceries Dataset. CoRR , Vol. abs\/ 1611 .05799 ( 2016 ). Philipp Jund, Nichola Abdo, Andreas Eitel, and Wolfram Burgard. 2016. The Freiburg Groceries Dataset. CoRR , Vol. abs\/1611.05799 (2016)."},{"key":"e_1_3_2_1_11_1","volume-title":"ACCV","volume":"2","author":"Koubaroulis D","year":"2002","unstructured":"D Koubaroulis , J Matas , J Kittler , and CTU CMP. 2002 . Evaluating colour-based object recognition algorithms using the soil-47 database . In ACCV , Vol. 2 . D Koubaroulis, J Matas, J Kittler, and CTU CMP. 2002. Evaluating colour-based object recognition algorithms using the soil-47 database. In ACCV , Vol. 2."},{"key":"e_1_3_2_1_12_1","unstructured":"Philipp Kr\"a henb\u00fc hl and Vladlen Koltun. 2011. Efficient Inference in Fully Connected CRFs with Gaussian Edge Potentials. In NeurIPS . 109--117.  Philipp Kr\"a henb\u00fc hl and Vladlen Koltun. 2011. Efficient Inference in Fully Connected CRFs with Gaussian Edge Potentials. In NeurIPS . 109--117."},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"crossref","unstructured":"Guanbin Li and Yizhou Yu. 2015. Visual saliency based on multiscale deep features. In CVPR. 5455--5463.  Guanbin Li and Yizhou Yu. 2015. Visual saliency based on multiscale deep features. In CVPR. 5455--5463.","DOI":"10.1109\/CVPR.2015.7299184"},{"key":"e_1_3_2_1_14_1","unstructured":"Yuhong Li Xiaofan Zhang and Deming Chen. 2018. CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes. In CVPR. 1091--1100.  Yuhong Li Xiaofan Zhang and Deming Chen. 2018. CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes. In CVPR. 1091--1100."},{"key":"e_1_3_2_1_15_1","volume-title":"Ross B. Girshick, Kaiming He, Bharath Hariharan, and Serge J. Belongie.","author":"Lin Tsung-Yi","year":"2017","unstructured":"Tsung-Yi Lin , Piotr Doll\u00e1 r , Ross B. Girshick, Kaiming He, Bharath Hariharan, and Serge J. Belongie. 2017 . Feature Pyramid Networks for Object Detection. In CVPR. 936--944. Tsung-Yi Lin, Piotr Doll\u00e1 r, Ross B. Girshick, Kaiming He, Bharath Hariharan, and Serge J. Belongie. 2017. Feature Pyramid Networks for Object Detection. In CVPR. 936--944."},{"key":"e_1_3_2_1_16_1","volume-title":"Piotr Doll\u00e1 r, and C. Lawrence Zitnick","author":"Lin Tsung-Yi","year":"2014","unstructured":"Tsung-Yi Lin , Michael Maire , Serge J. Belongie , James Hays , Pietro Perona , Deva Ramanan , Piotr Doll\u00e1 r, and C. Lawrence Zitnick . 2014 . Microsoft COCO: Common Objects in Context. In ECCV. 740--755. Tsung-Yi Lin, Michael Maire, Serge J. Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Doll\u00e1 r, and C. Lawrence Zitnick. 2014. Microsoft COCO: Common Objects in Context. In ECCV. 740--755."},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"crossref","unstructured":"Nian Liu and Junwei Han. 2016. DHSNet: Deep Hierarchical Saliency Network for Salient Object Detection. In CVPR . 678--686.  Nian Liu and Junwei Han. 2016. DHSNet: Deep Hierarchical Saliency Network for Salient Object Detection. In CVPR . 678--686.","DOI":"10.1109\/CVPR.2016.80"},{"key":"e_1_3_2_1_18_1","volume-title":"Belongie","author":"Merler Michele","year":"2007","unstructured":"Michele Merler , Carolina Galleguillos , and Serge J . Belongie . 2007 . Recognizing Groceries in situ Using in vitro Training Data. In CVPR . Michele Merler, Carolina Galleguillos, and Serge J. Belongie. 2007. Recognizing Groceries in situ Using in vitro Training Data. In CVPR ."},{"key":"e_1_3_2_1_19_1","volume-title":"NeurIPS Workshop .","author":"Paszke Adam","year":"2017","unstructured":"Adam Paszke , Sam Gross , Soumith Chintala , Gregory Chanan , Edward Yang , Zachary DeVito , Zeming Lin , Alban Desmaison , Luca Antiga , and Adam Lerer . 2017 . Automatic differentiation in PyTorch . In NeurIPS Workshop . Adam Paszke, Sam Gross, Soumith Chintala, Gregory Chanan, Edward Yang, Zachary DeVito, Zeming Lin, Alban Desmaison, Luca Antiga, and Adam Lerer. 2017. Automatic differentiation in PyTorch. In NeurIPS Workshop ."},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"crossref","unstructured":"Fan Qi Xiaoshan Yang and Changsheng Xu. 2018. A Unified Framework for Multimodal Domain Adaptation. In ACM Multimedia . 429--437.  Fan Qi Xiaoshan Yang and Changsheng Xu. 2018. A Unified Framework for Multimodal Domain Adaptation. In ACM Multimedia . 429--437.","DOI":"10.1145\/3240508.3240633"},{"key":"e_1_3_2_1_21_1","unstructured":"Shaoqing Ren Kaiming He Ross B. Girshick and Jian Sun. 2015. Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks. In NeurIPS . 91--99.  Shaoqing Ren Kaiming He Ross B. Girshick and Jian Sun. 2015. Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks. In NeurIPS . 91--99."},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.compag.2009.09.002"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-015-0816-y"},{"key":"e_1_3_2_1_24_1","unstructured":"Kuniaki Saito Yoshitaka Ushiku and Tatsuya Harada. 2017. Asymmetric Tri-training for Unsupervised Domain Adaptation. In ICML . 2988--2997.  Kuniaki Saito Yoshitaka Ushiku and Tatsuya Harada. 2017. Asymmetric Tri-training for Unsupervised Domain Adaptation. In ICML . 2988--2997."},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"crossref","unstructured":"Youbao Tang and Xiangqian Wu. 2017. Salient Object Detection with Chained Multi-Scale Fully Convolutional Network. In ACM Multimedia. 618--626.  Youbao Tang and Xiangqian Wu. 2017. Salient Object Detection with Chained Multi-Scale Fully Convolutional Network. In ACM Multimedia. 618--626.","DOI":"10.1145\/3123266.3123318"},{"key":"e_1_3_2_1_26_1","unstructured":"A\"a ron van den Oord Nal Kalchbrenner Lasse Espeholt Koray Kavukcuoglu Oriol Vinyals and Alex Graves. 2016. Conditional Image Generation with PixelCNN Decoders. In NeurIPS . 4790--4798.  A\"a ron van den Oord Nal Kalchbrenner Lasse Espeholt Koray Kavukcuoglu Oriol Vinyals and Alex Graves. 2016. Conditional Image Generation with PixelCNN Decoders. In NeurIPS . 4790--4798."},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.5555\/2627435.2697068"},{"key":"e_1_3_2_1_28_1","volume-title":"Yu","author":"Wang Jindong","year":"2018","unstructured":"Jindong Wang , Wenjie Feng , Yiqiang Chen , Han Yu , Meiyu Huang , and Philip S . Yu . 2018 . Visual Domain Adaptation with Manifold Embedded Distribution Alignment. In ACM Multimedia . 402--410. Jindong Wang, Wenjie Feng, Yiqiang Chen, Han Yu, Meiyu Huang, and Philip S. Yu. 2018. Visual Domain Adaptation with Manifold Embedded Distribution Alignment. In ACM Multimedia . 402--410."},{"key":"e_1_3_2_1_29_1","first-page":"251","article-title":"Salient Object Detection","volume":"123","author":"Wang Jingdong","year":"2017","unstructured":"Jingdong Wang , Huaizu Jiang , Zejian Yuan , Ming-Ming Cheng , Xiaowei Hu , and Nanning Zheng . 2017 . Salient Object Detection : A Discriminative Regional Feature Integration Approach. IJCV , Vol. 123 , 2 (2017), 251 -- 268 . Jingdong Wang, Huaizu Jiang, Zejian Yuan, Ming-Ming Cheng, Xiaowei Hu, and Nanning Zheng. 2017. Salient Object Detection: A Discriminative Regional Feature Integration Approach. IJCV , Vol. 123, 2 (2017), 251--268.","journal-title":"A Discriminative Regional Feature Integration Approach. IJCV"},{"key":"e_1_3_2_1_30_1","volume-title":"RPC: A Large-Scale Retail Product Checkout Dataset. CoRR","author":"Wei Xiu-Shen","year":"2019","unstructured":"Xiu-Shen Wei , Quan Cui , Lei Yang , Peng Wang , and Lingqiao Liu . 2019 . RPC: A Large-Scale Retail Product Checkout Dataset. CoRR , Vol. abs\/ 1901 .07249 (2019). Xiu-Shen Wei, Quan Cui, Lei Yang, Peng Wang, and Lingqiao Liu. 2019. RPC: A Large-Scale Retail Product Checkout Dataset. CoRR , Vol. abs\/1901.07249 (2019)."},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"crossref","unstructured":"Xinchen Yan Jimei Yang Kihyuk Sohn and Honglak Lee. 2016. Attribute2Image: Conditional Image Generation from Visual Attributes. In ECCV . 776--791.  Xinchen Yan Jimei Yang Kihyuk Sohn and Honglak Lee. 2016. Attribute2Image: Conditional Image Generation from Visual Attributes. In ECCV . 776--791.","DOI":"10.1007\/978-3-319-46493-0_47"},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"crossref","unstructured":"Yingying Zhang Desen Zhou Siqin Chen Shenghua Gao and Yi Ma. 2016. Single-Image Crowd Counting via Multi-Column Convolutional Neural Network. In CVPR . 589--597.  Yingying Zhang Desen Zhou Siqin Chen Shenghua Gao and Yi Ma. 2016. Single-Image Crowd Counting via Multi-Column Convolutional Neural Network. In CVPR . 589--597.","DOI":"10.1109\/CVPR.2016.70"},{"key":"e_1_3_2_1_33_1","volume-title":"Efros","author":"Zhu Jun-Yan","year":"2017","unstructured":"Jun-Yan Zhu , Taesung Park , Phillip Isola , and Alexei A . Efros . 2017 . Unpaired Image-to-Image Translation Using Cycle-Consistent Adversarial Networks. In ICCV . 2242--2251. Jun-Yan Zhu, Taesung Park, Phillip Isola, and Alexei A. Efros. 2017. Unpaired Image-to-Image Translation Using Cycle-Consistent Adversarial Networks. In ICCV . 2242--2251."}],"event":{"name":"MM '19: The 27th ACM International Conference on Multimedia","sponsor":["SIGMM ACM Special Interest Group on Multimedia"],"location":"Nice France","acronym":"MM '19"},"container-title":["Proceedings of the 27th ACM International Conference on Multimedia"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3343031.3350989","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3343031.3350989","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T23:13:18Z","timestamp":1750201998000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3343031.3350989"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,10,15]]},"references-count":33,"alternative-id":["10.1145\/3343031.3350989","10.1145\/3343031"],"URL":"https:\/\/doi.org\/10.1145\/3343031.3350989","relation":{},"subject":[],"published":{"date-parts":[[2019,10,15]]},"assertion":[{"value":"2019-10-15","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}