{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/where-is-misty-interpreting-spatial","title":"Where is Misty? Interpreting Spatial Descriptors by Modeling Regions in Space","arxiv_id":null,"date":"2017-09-01","proceeding":"EMNLP 2017 9","authors":["Nikita Kitaev","Dan Klein"],"abstract":"We present a model for locating regions in space based on natural language descriptions. Starting with a 3D scene and a sentence, our model is able to associate words in the sentence with regions in the scene, interpret relations such as {`}on top of{'} or {`}next to,{'} and finally locate the region described in the sentence. All components form a single neural network that is trained end-to-end without prior knowledge of object segmentation. To evaluate our model, we construct and release a new dataset consisting of Minecraft scenes with crowdsourced natural language descriptions. We achieve a 32{\\%} relative error reduction compared to a strong neural baseline.","url_abs":"https://aclanthology.org/D17-1015","url_pdf":"https://aclanthology.org/D17-1015.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"where-is-misty-interpreting-spatial","repo_url":"https://github.com/nikitakit/voxelworld","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"tf","reach":null}],"tasks":[{"task_slug":"minecraft","task_name":"Minecraft"},{"task_slug":"semantic-segmentation","task_name":"Semantic Segmentation"},{"task_slug":"sentence","task_name":"Sentence"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}