English
Related papers

Related papers: StoryBench: A Multifaceted Benchmark for Continuou…

200 papers

We present an efficient framework that can generate a coherent paragraph to describe a given video. Previous works on video captioning usually focus on video clips. They typically treat an entire video as a whole and generate the caption…

Computer Vision and Pattern Recognition · Computer Science 2018-07-27 Yilei Xiong , Bo Dai , Dahua Lin

Recent advances in generative foundational models, often termed "world models," have propelled interest in applying them to critical tasks like robotic planning and autonomous system training. For reliable deployment, these models must…

Computer Vision and Pattern Recognition · Computer Science 2026-01-30 Rishi Upadhyay , Howard Zhang , Jim Solomon , Ayush Agrawal , Pranay Boreddy , Shruti Satya Narayana , Yunhao Ba , Alex Wong , Celso M de Melo , Achuta Kadambi

Generative models have driven significant progress in a variety of AI tasks, including text-to-video generation, where models like Video LDM and Stable Video Diffusion can produce realistic, movie-level videos from textual instructions.…

Computer Vision and Pattern Recognition · Computer Science 2025-04-08 Xuyang Guo , Zekai Huang , Jiayan Huo , Yingyu Liang , Zhenmei Shi , Zhao Song , Jiahao Zhang

Video understanding, including video captioning and retrieval, is still a great challenge for video-language models (VLMs). The existing video retrieval and caption benchmarks only include short descriptions, limits their ability of…

Computer Vision and Pattern Recognition · Computer Science 2025-03-19 Yifan Xu , Xinhao Li , Yichun Yang , Desen Meng , Rui Huang , Limin Wang

Real-world videos often have complex dynamics; and methods for generating open-domain video descriptions should be sensitive to temporal structure and allow both input (sequence of frames) and output (sequence of words) of variable length.…

Computer Vision and Pattern Recognition · Computer Science 2015-10-20 Subhashini Venugopalan , Marcus Rohrbach , Jeff Donahue , Raymond Mooney , Trevor Darrell , Kate Saenko

With the rapid growth of video centered social media, the ability to anticipate risky events from visual data is a promising direction for ensuring public safety and preventing real world accidents. Prior work has extensively studied…

Computer Vision and Pattern Recognition · Computer Science 2026-01-22 Sha Luo , Yogesh Prabhu , Timothy Ossowski , Kaiping Chen , Junjie Hu

Text-to-video generation task has witnessed a notable progress, with the generated outcomes reflecting the text prompts with high fidelity and impressive visual qualities. However, current text-to-video generation models are invariably…

Computer Vision and Pattern Recognition · Computer Science 2024-05-15 Andrew Shin , Yusuke Mori , Kunitake Kaneko

Visual storytelling aims to generate a narrative paragraph from a sequence of images automatically. Existing approaches construct text description independently for each image and roughly concatenate them as a story, which leads to the…

Computation and Language · Computer Science 2020-11-02 Ruize Wang , Zhongyu Wei , Ying Cheng , Piji Li , Haijun Shan , Ji Zhang , Qi Zhang , Xuanjing Huang

Recent progress in multimodal large language models has markedly enhanced the understanding of short videos (typically under one minute), and several evaluation datasets have emerged accordingly. However, these advancements fall short of…

Computer Vision and Pattern Recognition · Computer Science 2025-08-12 Weihan Wang , Zehai He , Wenyi Hong , Yean Cheng , Xiaohan Zhang , Ji Qi , Xiaotao Gu , Shiyu Huang , Bin Xu , Yuxiao Dong , Ming Ding , Jie Tang

The surging demand for adapting long-form cinematic content into short videos has motivated the need for versatile automatic video compilation systems. However, existing compilation methods are limited to predefined tasks, and the community…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Peixuan Zhang , Chang Zhou , Ziyuan Zhang , Hualuo Liu , Chunjie Zhang , Jingqi Liu , Xiaohui Zhou , Xi Chen , Shuchen Weng , Si Li , Boxin Shi

Multimodal Large Language Models (MLLMs) have advanced in integrating diverse modalities but frequently suffer from hallucination. A promising solution to mitigate this issue is to generate text with citations, providing a transparent chain…

Computation and Language · Computer Science 2025-05-21 Caiyu Hu , Yikai Zhang , Tinghui Zhu , Yiwei Ye , Yanghua Xiao

Training-free consistent text-to-image generation depicting the same subjects across different images is a topic of widespread recent interest. Existing works in this direction predominantly rely on cross-frame self-attention; which…

Computer Vision and Pattern Recognition · Computer Science 2025-04-09 Jaskirat Singh , Junshen Kevin Chen , Jonas Kohler , Michael Cohen

Querying generative AI models, e.g., large language models (LLMs), has become a prevalent method for information acquisition. However, existing query-answer datasets primarily focus on textual responses, making it challenging to address…

Artificial Intelligence · Computer Science 2025-06-03 Shuting Wang , Yunqi Liu , Zixin Yang , Ning Hu , Zhicheng Dou , Chenyan Xiong

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

Media editors in the newsroom are constantly pressed to provide a "like-being there" coverage of live events. Social media provides a disorganised collection of images and videos that media professionals need to grasp before publishing…

Multimedia · Computer Science 2019-08-12 Gonçalo Marcelino , David Semedo , André Mourão , Saverio Blasi , Marta Mrak , João Magalhães

Video foundation models aim to integrate video understanding, generation, editing, and instruction following within a single framework, making them a central direction for next-generation multimodal systems. However, existing evaluation…

Computer Vision and Pattern Recognition · Computer Science 2026-03-09 Jianhui Wei , Xiaotian Zhang , Yichen Li , Yuan Wang , Yan Zhang , Ziyi Chen , Zhihang Tang , Wei Xu , Zuozhu Liu

Understanding video content and generating caption with context is an important and challenging task. Unlike prior methods that typically attempt to generate generic video captions without context, our architecture contextualizes captioning…

Computer Vision and Pattern Recognition · Computer Science 2020-07-30 Philipp Rimle , Pelin Dogan , Markus Gross

The comprehension of text-rich visual scenes has become a focal point for evaluating Multi-modal Large Language Models (MLLMs) due to their widespread applications. Current benchmarks tailored to the scenario emphasize perceptual…

Computer Vision and Pattern Recognition · Computer Science 2024-10-16 Bin Shan , Xiang Fei , Wei Shi , An-Lan Wang , Guozhi Tang , Lei Liao , Jingqun Tang , Xiang Bai , Can Huang

Text-to-video generative models have made significant strides in recent years, producing high-quality videos that excel in both aesthetic appeal and accurate instruction following, and have become central to digital art creation and user…

Machine Learning · Computer Science 2025-05-02 Xuyang Guo , Jiayan Huo , Zhenmei Shi , Zhao Song , Jiahao Zhang , Jiale Zhao

The goal of this work is to generate step-by-step visual instructions in the form of a sequence of images, given an input image that provides the scene context and the sequence of textual instructions. This is a challenging problem as it…

Computer Vision and Pattern Recognition · Computer Science 2025-03-26 Tomáš Souček , Prajwal Gatti , Michael Wray , Ivan Laptev , Dima Damen , Josef Sivic