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ImageNet Large Scale Visual Recognition Challenge, , , , , , , , , and 2 other author(s). (2014)cite arxiv:1409.0575Comment: 43 pages, 16 figures. v3 includes additional comparisons with PASCAL VOC (per-category comparisons in Table 3, distribution of localization difficulty in Fig 16), a list of queries used for obtaining object detection images (Appendix C), and some additional references.Low Power Inference for On-Device Visual Recognition with a Quantization-Friendly Solution., , , , , , , , , and 2 other author(s). CoRR, (2019)Combining Multiple Cues for Visual Madlibs Question Answering., , , , , and . Int. J. Comput. Vis., 127 (1): 38-60 (2019)Hipster Wars: Discovering Elements of Fashion Styles., , , and . ECCV (1), volume 8689 of Lecture Notes in Computer Science, page 472-488. Springer, (2014)Learning from Models and Data for Visual Grounding., , , , and . CoRR, (2024)Solving VIsual Madlibs with Multiple Cues., , , , , and . BMVC, BMVA Press, (2016)Synthesizing Training Data for Object Detection in Indoor Scenes., , , and . Robotics: Science and Systems, (2017)Geometric Blur for Template Matching., and . CVPR (1), page 607-614. IEEE Computer Society, (2001)Parsing Images of Architectural Scenes., , and . ICCV, page 1-8. IEEE Computer Society, (2007)Recovering Human Body Configurations Using Pairwise Constraints between Parts., , and . ICCV, page 824-831. IEEE Computer Society, (2005)