tailieunhanh - Báo cáo khoa học: "Generating Image Descriptions From Computer Vision Detections"

This paper introduces a novel generation system that composes humanlike descriptions of images from computer vision detections. By leveraging syntactically informed word co-occurrence statistics, the generator filters and constrains the noisy detections output from a vision system to generate syntactic trees that detail what the computer vision system sees. Results show that the generation system outperforms state-of-the-art systems, automatically generating some of the most natural image descriptions to date. . | Midge Generating Image Descriptions From Computer Vision Detections Margaret Mitchelứ Jesse Dodge Amit Goyaltt Kota Yamaguchi Karl Stratos Xufeng Han Alyssa Mensch Alex Berg Tamara Berg Hal Daume Illtt U. of Aberdeen and Oregon Health and Science University Stony Brook University aberg tlberg xufhan kyamagu @ U. of Maryland hal amit @ H Columbia University stratos@ U. of Washington dodgejesse@ MIT acmensch@ Abstract This paper introduces a novel generation system that composes humanlike descriptions of images from computer vision detections. By leveraging syntactically informed word co-occurrence statistics the generator filters and constrains the noisy detections output from a vision system to generate syntactic trees that detail what the computer vision system sees. Results show that the generation system outperforms state-of-the-art systems automatically generating some of the most natural image descriptions to date. 1 Introduction It is becoming a real possibility for intelligent systems to talk about the visual world. New ways of mapping computer vision to generated language have emerged in the past few years with a focus on pairing detections in an image to words Farhadi et al. 2010 Li et al. 2011 Kulkarni et al. 2011 Yang et al. 2011 . The goal in connecting vision to language has varied systems have started producing language that is descriptive and poetic Li et al. 2011 summaries that add content where the computer vision system does not Yang et al. 2011 and captions copied directly from other images that are globally Farhadi et al. 2010 and locally similar Ordonez et al. 2011 . A commonality between all of these approaches is that they aim to produce naturalsounding descriptions from computer vision detections. This commonality is our starting point We aim to design a system capable of producing natural-sounding descriptions from computer vision detections that are .

• Báo cáo khoa học
• Generating Image Descriptions
• Computer Vision Detections
• Margaret Mitchell
• scientific reports
• model language
• process natural language
• dependency relational patterns
• Long Papers
• báo cáo khoa học
• báo cáo ngôn ngữ
• ngôn ngữ tự nhiên
• Dialog Control
• Natural Language System
• Dialog Control in a Natural Language System
• Expanding the Horizons
• Natural Language Interfaces
• Phil Hayes
• PROSPECTS OR PRACTICAL
• NATURAL LANGUAGE SYSTEMS
• Workshops
• NATURAL LANGUAGE
• INTERACTION WITH MACHINES
• COMPUTER INTEBFACE DESIGN MURRAY TUROFF DEPARTMENT OF COMPUTER
• IiVFORMATION SCIENCE IIEW JERSEY INSTITUTE OF TECHNOLOGY
• EVALUATION OF NATURAL LANGUAGE
• INTERFACES TO DATABASE SYSTEMS
• A PANEL DISCUSSION
• database query system
• J
• Norwood Crout
• INTERFACES TO DATA BASE SYSTEMS
• Bozena Henisz
• INTERPRETING NATURAL LANGUAGE
• DATABASE UPDATES
• S
• Jermld Kaplan Jim David
• TRANSPORTABLE NATURAL LANGUAGE
• INTERFACES TO DATABASES
• Gary G
• Hendrlx and William H
• Lewis
• DATABASES THEORETICAL
• TECHNICAL ISSUES
• TRANSPORTABLE NATURAL LANGUAGE INTERFACES
• PROBLEMS AND TECHNIQUES
• Barbara J
• Grosz
• THEORETICAL TECHNICAL ISSUES
• NATURAL LANGUAGE ACCESS TO DATABASES
• R
• Petrick
• Domain Independent
• Database Access Systems
• ISSUES IN NATURAL LANGUAGE
• ACCESS TO DATABASES
• A LOGIC PROGRAMMING PERSPECTIVE
• Sharon C
• Salveter David Maier
• PLANNING NATURAL LANGUAGE
• EXPRESSIONS REFERRING
• Douglas E
• Appelt
• THE TEXT SYSTEM
• NATURAL LANGUAGE GENERATION
• Kathleen R
• M
• MENTING A DATABASE
• KNOWLEDGE REPRESENTATION
• THE KEY TO THE SELECTION PROBLEM
• E
• Jeffrey Conklin David D
• McDonald
• A KNOWLEDGE ENGINEERING
• NATURAL LANGUAGE UNDERSTANDING
• Stuart C
• Shapiro
• NATURAL LANGUAGE TEXTS
• NECESSARILY GRAMMATICAL
• EVEN COMPLETE
• UNGRAMHATICALITY
• EXTRA GRAMMATICALITY
• NATURAL LANGUAGE UNDERSTANDING SYSTEMS
• Taxonomy
• Descriptions
• Individuals in Natural
• Language Understanding
• The Use of Ooject Special Knowledge
• Natural Language Processing
• Mark H
• Bursteln