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In this paper, we introduce DirectorLLM, a novel video generation model that employs a large language model (LLM) to orchestrate human poses within videos. As foundational text-to-video models rapidly evolve, the demand for high-quality…

Temporal Sentence Grounding (TSG), which aims to localize moments from videos based on the given natural language queries, has attracted widespread attention. Existing works are mainly designed for short videos, failing to handle TSG in…

计算机视觉与模式识别 · 计算机科学 2023-12-29 Houlun Chen , Xin Wang , Hong Chen , Zihan Song , Jia Jia , Wenwu Zhu

Current autoregressive diffusion models excel at video generation but are generally limited to short temporal durations. Our theoretical analysis indicates that the autoregressive modeling typically suffers from temporal drift caused by…

计算机视觉与模式识别 · 计算机科学 2025-10-15 Xunzhi Xiang , Yabo Chen , Guiyu Zhang , Zhongyu Wang , Zhe Gao , Quanming Xiang , Gonghu Shang , Junqi Liu , Haibin Huang , Yang Gao , Chi Zhang , Qi Fan , Xuelong Li

Video Large Language Models (Video-LLMs) have shown strong video understanding, yet their application to long-form videos remains constrained by limited context windows. A common workaround is to compress long videos into a handful of…

计算机视觉与模式识别 · 计算机科学 2026-03-10 Yun Wang , Long Zhang , Jingren Liu , Jiaqi Yan , Zhanjie Zhang , Jiahao Zheng , Ao Ma , Run Ling , Xun Yang , Dapeng Wu , Xiangyu Chen , Xuelong Li

Recent progress in large models has led to significant advances in unified multimodal generation and understanding. However, the development of models that unify motion-language generation and understanding remains largely underexplored.…

计算机视觉与模式识别 · 计算机科学 2026-04-20 Zekun Li , Sizhe An , Chengcheng Tang , Chuan Guo , Ivan Shugurov , Linguang Zhang , Amy Zhao , Srinath Sridhar , Lingling Tao , Abhay Mittal

Large Language Models (LLM) are already widely used to generate content for a variety of online platforms. As we are not able to safely distinguish LLM-generated content from human-produced content, LLM-generated content is used to train…

机器学习 · 计算机科学 2024-06-18 Martin Briesch , Dominik Sobania , Franz Rothlauf

Short-form videos are gaining popularity in education due to their concise and accessible format that enables microlearning. Yet, most of these videos are manually created. Even for those automatically generated using artificial…

Current video-language models struggle with long-video understanding due to limited context lengths and reliance on sparse frame subsampling, often leading to information loss. This paper introduces $\infty$-Video, which can process…

计算机视觉与模式识别 · 计算机科学 2025-05-20 Saul Santos , António Farinhas , Daniel C. McNamee , André F. T. Martins

Trailers are short promotional videos designed to provide audiences with a glimpse of a movie. The process of creating a trailer typically involves selecting key scenes, dialogues and action sequences from the main content and editing them…

多媒体 · 计算机科学 2026-02-02 Roberto Balestri , Pasquale Cascarano , Mirko Degli Esposti , Guglielmo Pescatore

Retrieval-Augmented Generation (RAG) has demonstrated remarkable success in enhancing Large Language Models (LLMs) through external knowledge integration, yet its application has primarily focused on textual content, leaving the rich domain…

信息检索 · 计算机科学 2025-02-04 Xubin Ren , Lingrui Xu , Long Xia , Shuaiqiang Wang , Dawei Yin , Chao Huang

One critical prerequisite for faithful text-to-image generation is the accurate understanding of text inputs. Existing methods leverage the text encoder of the CLIP model to represent input prompts. However, the pre-trained CLIP model can…

计算机视觉与模式识别 · 计算机科学 2024-07-19 Zhiyu Tan , Mengping Yang , Luozheng Qin , Hao Yang , Ye Qian , Qiang Zhou , Cheng Zhang , Hao Li

As text generation has become a core capability of modern Large Language Models (LLMs), it underpins a wide range of downstream applications. However, most existing LLMs rely on autoregressive (AR) generation, producing one token at a time…

This paper presents VideoStreaming, an advanced vision-language large model (VLLM) for video understanding, that capably understands arbitrary-length video with a constant number of video tokens streamingly encoded and adaptively selected.…

计算机视觉与模式识别 · 计算机科学 2024-05-28 Rui Qian , Xiaoyi Dong , Pan Zhang , Yuhang Zang , Shuangrui Ding , Dahua Lin , Jiaqi Wang

Learning multimodal video understanding typically relies on datasets comprising video clips paired with manually annotated captions. However, this becomes even more challenging when dealing with long-form videos, lasting from minutes to…

计算机视觉与模式识别 · 计算机科学 2025-03-12 Soumya Shamarao Jahagirdar , Jayasree Saha , C V Jawahar

Rapid advancements have been made in extending Large Language Models (LLMs) to Large Multi-modal Models (LMMs). However, extending input modality of LLMs to video data remains a challenging endeavor, especially for long videos. Due to…

计算机视觉与模式识别 · 计算机科学 2024-08-29 Jiajun Liu , Yibing Wang , Hanghang Ma , Xiaoping Wu , Xiaoqi Ma , Xiaoming Wei , Jianbin Jiao , Enhua Wu , Jie Hu

Driven by the wave of large language models, Video-Language Models (VLMs) have become a significant yet challenging technology to bridge the gap between videos and texts. Although previous VLM works have made significant progress, almost…

计算机视觉与模式识别 · 计算机科学 2026-05-28 Xiang Fang , Wanlong Fang , Changshuo Wang , Xiaoye Qu , Daizong Liu

Virtual Reality (VR) has emerged as a powerful tool for workforce training, offering immersive, interactive, and risk-free environments that enhance skill acquisition, decision-making, and confidence. Despite its advantages, developing VR…

计算机视觉与模式识别 · 计算机科学 2025-08-07 Subin Raj Peter

Significant progress has been made in text-to-video generation through the use of powerful generative models and large-scale internet data. However, substantial challenges remain in precisely controlling individual concepts within the…

计算机视觉与模式识别 · 计算机科学 2024-09-30 Hanxin Zhu , Tianyu He , Anni Tang , Junliang Guo , Zhibo Chen , Jiang Bian

3D content creation has achieved significant progress in terms of both quality and speed. Although current feed-forward models can produce 3D objects in seconds, their resolution is constrained by the intensive computation required during…

计算机视觉与模式识别 · 计算机科学 2024-02-08 Jiaxiang Tang , Zhaoxi Chen , Xiaokang Chen , Tengfei Wang , Gang Zeng , Ziwei Liu

We propose VideoPerceiver, a novel video multimodal large language model (VMLLM) that enhances fine-grained perception in video understanding, addressing VMLLMs' limited ability to reason about brief actions in short clips or rare transient…

计算机视觉与模式识别 · 计算机科学 2025-11-25 Fufangchen Zhao , Liao Zhang , Daiqi Shi , Yuanjun Gao , Chen Ye , Yang Cai , Jian Gao , Danfeng Yan