IMAGE STORY: ENHANCED COGNITIVE VISUAL NARRATIVE SYSTEM

This paper presents the Enhanced Cognitive Visual Narrative System (ECVNS), a sophisticated multi-modal artificial intelligence framework designed for automated visual storytelling. The system integrates multiple state-of-the-art deep learning models including OWLv2for object detection, BLIP for image captioning and visual question answering, CLIP for emotional analysis, and ViLT for scene understanding. The framework demonstrates the capability to generate coherent, contextually relevant narratives in six languages based on comprehensive visual analysis. Our approach combines computer vision techniques with natural language generation to create a unified system that can understand visual content at multiple semantic levels and translate this understanding into creative storytelling. The system achieves high accuracy in object detection, scene understanding, and emotional inference, resulting in narratives that demonstrate both technical precision and creative quality. This work contributes to the advancing field of multimodal AI and has applications in content creation, accessibility, education, and entertainment.

Authors

Publication Details

Journal
International Journal of Advanced Research
Published
2025-06-30
DOI
https://doi.org/10.21474/ijar01/21185
Primary Topic
Video Analysis and Summarization
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

IMAGE STORY: ENHANCED COGNITIVE VISUAL NARRATIVE SYSTEM

Ashutosh Kumar Singh, Atish Khobragade, Vikas Kanake
International Journal of Advanced Research
Video Analysis and Summarization
article

IMAGE STORY: ENHANCED COGNITIVE VISUAL NARRATIVE SYSTEM

Ashutosh Kumar Singh, Atish Khobragade, Vikas Kanake
article en

Abstract

This paper presents the Enhanced Cognitive Visual Narrative System (ECVNS), a sophisticated multi-modal artificial intelligence framework designed for automated visual storytelling. The system integrates multiple state-of-the-art deep learning models including OWLv2for object detection, BLIP for image captioning and visual question answering, CLIP for emotional analysis, and ViLT for scene understanding. The framework demonstrates the capability to generate coherent, contextually relevant narratives in six languages based on comprehensive visual analysis. Our approach combines computer vision techniques with natural language generation to create a unified system that can understand visual content at multiple semantic levels and translate this understanding into creative storytelling. The system achieves high accuracy in object detection, scene understanding, and emotional inference, resulting in narratives that demonstrate both technical precision and creative quality. This work contributes to the advancing field of multimodal AI and has applications in content creation, accessibility, education, and entertainment.

International Journal of Advanced ResearchVol. 13(06)
Openalex Percentile: Top 85%
Video Analysis and Summarization
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

IMAGE STORY: ENHANCED COGNITIVE VISUAL NARRATIVE SYSTEM — Ashutosh Kumar Singh, Atish Khobragade, et al. · International Journal of Advanced Research (2025) | TGRS Research Map | TGRS