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Visual narrative generation transforms textual narratives into sequences of images illustrating the content of the text. However, generating visual narratives that are faithful to the input text and self-consistent across generated images…

Computer Vision and Pattern Recognition · Computer Science 2025-04-04 Silin Gao , Sheryl Mathew , Li Mi , Sepideh Mamooler , Mengjie Zhao , Hiromi Wakaki , Yuki Mitsufuji , Syrielle Montariol , Antoine Bosselut

Existing approaches for digital short-drama production typically rely on one-shot LLM generated scripts and loosely coupled pipelines, which fail to satisfy three key requirements of short-drama generation: (1) narrative pacing, resulting…

Computer Vision and Pattern Recognition · Computer Science 2026-05-22 Yufei Shi , Weilong Yan , Naixuan Huang , Yucheng Chen , Chenyu Zhang , Tao He , Si Yong Yeo , Ming Li

The rapid evolution of Large Language Models (LLMs) has fostered diverse paradigms for automated slide generation, ranging from code-driven layouts to image-centric synthesis. However, evaluating these heterogeneous systems remains…

Computation and Language · Computer Science 2026-01-15 Yunqiao Yang , Wenbo Li , Houxing Ren , Zimu Lu , Ke Wang , Zhiyuan Huang , Zhuofan Zong , Mingjie Zhan , Hongsheng Li

Recent advances in video generation have been remarkable, enabling models to produce visually compelling videos with synchronized audio. While existing video generation benchmarks provide comprehensive metrics for visual quality, they lack…

Computer Vision and Pattern Recognition · Computer Science 2026-04-07 Daili Hua , Xizhi Wang , Bohan Zeng , Xinyi Huang , Hao Liang , Junbo Niu , Xinlong Chen , Quanqing Xu , Wentao Zhang

Generating long, cohesive video stories with consistent characters is a significant challenge for current text-to-video AI. We introduce a method that approaches video generation in a filmmaker-like manner. Instead of creating a video in…

Computer Vision and Pattern Recognition · Computer Science 2025-12-22 Chayan Jain , Rishant Sharma , Archit Garg , Ishan Bhanuka , Pratik Narang , Dhruv Kumar

The rapid advancement of AIGC-based video generation has underscored the critical need for comprehensive evaluation frameworks that go beyond traditional generation quality metrics to encompass aesthetic appeal. However, existing benchmarks…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Longteng Jiang , DanDan Zheng , Qianqian Qiao , Heng Huang , Huaye Wang , Yihang Bo , Bao Peng , Jingdong Chen , Jun Zhou , Xin Jin

The rapid advancement of video generation models has made it increasingly challenging to distinguish AI-generated videos from real ones. This issue underscores the urgent need for effective AI-generated video detectors to prevent the…

Computer Vision and Pattern Recognition · Computer Science 2026-03-02 Zhenliang Ni , Qiangyu Yan , Mouxiao Huang , Tianning Yuan , Yehui Tang , Hailin Hu , Xinghao Chen , Yunhe Wang

While current video generation focuses on text or image conditions, practical applications like video editing and vlogging often need to seamlessly connect separate clips. In our work, we introduce Video Connecting, an innovative task that…

Computer Vision and Pattern Recognition · Computer Science 2026-01-28 Zhiyu Yin , Zhipeng Liu , Kehai Chen , Lemao Liu , Jin Liu , Hong-Dong Li , Yang Xiang , Min Zhang

Long-term agent memory is increasingly multimodal, yet existing evaluations rarely test whether agents preserve the visual evidence needed for later reasoning. In prior work, many visually grounded questions can be answered using only…

Long-term memory is fundamental for personalized agents capable of accumulating knowledge, reasoning over user experiences, and adapting across time. However, existing memory benchmarks primarily target declarative memory, specifically…

We present a unified network for simultaneously generating videos and their corresponding entity segmentation and depth maps from text prompts. We utilize colormap to represent entity masks and depth maps, tightly integrating dense…

Computer Vision and Pattern Recognition · Computer Science 2025-03-13 Lehan Yang , Lu Qi , Xiangtai Li , Sheng Li , Varun Jampani , Ming-Hsuan Yang

With the growing demand for intelligent in-vehicle experiences, vehicle-based agents are evolving from simple assistants to long-term companions. This evolution requires agents to continuously model multi-user preferences and make reliable…

Artificial Intelligence · Computer Science 2026-03-26 Yuhao Chen , Yi Xu , Xinyun Ding , Xiang Fang , Shuochen Liu , Luxi Lin , Qingyu Zhang , Ya Li , Quan Liu , Tong Xu

Podcast script generation requires LLMs to synthesize structured, context-grounded dialogue from diverse inputs, yet systematic evaluation resources for this task remain limited. To bridge this gap, we introduce PodBench, a benchmark…

Computation and Language · Computer Science 2026-01-22 Chenning Xu , Mao Zheng , Mingyu Zheng , Mingyang Song

Multimodal Large Language Models have achieved strong performance in single-video understanding, yet their ability to reason across multiple videos remains limited. Existing approaches typically concatenate multiple videos into a single…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Yue Zhang , Liqiang Jing , Jia Li , Yapeng Tian , Xinya Du , Yunhui Guo , Vibhav Gogate

Cinematography, the fundamental visual language of film, is essential for conveying narrative, emotion, and aesthetic quality. While recent Vision-Language Models (VLMs) demonstrate strong general visual understanding, their proficiency in…

Computer Vision and Pattern Recognition · Computer Science 2026-03-31 Hongbo Liu , Jingwen He , Yi Jin , Dian Zheng , Yuhao Dong , Fan Zhang , Ziqi Huang , Yinan He , Yangguang Li , Weichao Chen , Yu Qiao , Wanli Ouyang , Shengjie Zhao , Ziwei Liu

Video Large Language Models (VideoLLMs) have demonstrated remarkable understanding capabilities, but are found struggling to tackle multi-shot scenarios,e.g., video clips with varying camera angles or scene changes. This challenge can…

Computer Vision and Pattern Recognition · Computer Science 2025-07-09 Yujia Liang , Jile Jiao , Xuetao Feng , Zixuan Ye , Yuan Wang , Zhicheng Wang

The continuous development of foundational models for video generation is evolving into various applications, with subject-consistent video generation still in the exploratory stage. We refer to this as Subject-to-Video, which extracts…

Computer Vision and Pattern Recognition · Computer Science 2025-04-11 Lijie Liu , Tianxiang Ma , Bingchuan Li , Zhuowei Chen , Jiawei Liu , Gen Li , Siyu Zhou , Qian He , Xinglong Wu

Generating multi-view images based on text or single-image prompts is a critical capability for the creation of 3D content. Two fundamental questions on this topic are what data we use for training and how to ensure multi-view consistency.…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Qi Zuo , Xiaodong Gu , Lingteng Qiu , Yuan Dong , Zhengyi Zhao , Weihao Yuan , Rui Peng , Siyu Zhu , Zilong Dong , Liefeng Bo , Qixing Huang

Recent advancements in image generation models have enabled the prediction of future Graphical User Interface (GUI) states based on user instructions. However, existing benchmarks primarily focus on general domain visual fidelity, leaving…

Humans share a strong tendency to memorize/forget some of the visual information they encounter. This paper focuses on providing computational models for the prediction of the intrinsic memorability of visual content. To address this new…

Computer Vision and Pattern Recognition · Computer Science 2024-02-28 Romain Cohendet , Claire-Hélène Demarty , Ngoc Q. K. Duong , Martin Engilberge
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