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Advances in GPT-based large language models (LLMs) are revolutionizing natural language processing, exponentially increasing its use across various domains. Incorporating uni-directional attention, these autoregressive LLMs can generate…

Computer Vision and Pattern Recognition · Computer Science 2023-07-25 Lalithkumar Seenivasan , Mobarakol Islam , Gokul Kannan , Hongliang Ren

Multistep instructions, such as recipes and how-to guides, greatly benefit from visual aids, such as a series of images that accompany the instruction steps. While Large Language Models (LLMs) have become adept at generating coherent…

Computer Vision and Pattern Recognition · Computer Science 2024-05-17 João Bordalo , Vasco Ramos , Rodrigo Valério , Diogo Glória-Silva , Yonatan Bitton , Michal Yarom , Idan Szpektor , Joao Magalhaes

With the impressive progress in diffusion-based text-to-image generation, extending such powerful generative ability to text-to-video raises enormous attention. Existing methods either require large-scale text-video pairs and a large number…

Computer Vision and Pattern Recognition · Computer Science 2023-10-18 Ruiqi Wu , Liangyu Chen , Tong Yang , Chunle Guo , Chongyi Li , Xiangyu Zhang

Text-to-video generation models have shown significant progress in the recent years. However, they still struggle with generating complex dynamic scenes based on compositional text prompts, such as attribute binding for multiple objects,…

Computer Vision and Pattern Recognition · Computer Science 2024-12-06 Kaiyi Huang , Yukun Huang , Xuefei Ning , Zinan Lin , Yu Wang , Xihui Liu

Generating consistent long videos is a complex challenge: while diffusion-based generative models generate visually impressive short clips, extending them to longer durations often leads to memory bottlenecks and long-term inconsistency. In…

Computer Vision and Pattern Recognition · Computer Science 2025-07-22 Wenqi Ouyang , Zeqi Xiao , Danni Yang , Yifan Zhou , Shuai Yang , Lei Yang , Jianlou Si , Xingang Pan

Event cameras record visual information as asynchronous pixel change streams, excelling at scene perception under unsatisfactory lighting or high-dynamic conditions. Existing multimodal large language models (MLLMs) concentrate on natural…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Shaoyu Liu , Jianing Li , Guanghui Zhao , Yunjian Zhang , Xin Meng , Fei Richard Yu , Xiangyang Ji , Ming Li

Generating and editing a 3D scene guided by natural language poses a challenge, primarily due to the complexity of specifying the positional relations and volumetric changes within the 3D space. Recent advancements in Large Language Models…

Computer Vision and Pattern Recognition · Computer Science 2023-05-26 Yiqi Lin , Hao Wu , Ruichen Wang , Haonan Lu , Xiaodong Lin , Hui Xiong , Lin Wang

Current video generation models produce physically inconsistent motion that violates real-world dynamics. We propose TrajVLM-Gen, a two-stage framework for physics-aware image-to-video generation. First, we employ a Vision Language Model to…

Computer Vision and Pattern Recognition · Computer Science 2025-10-02 Fan Yang , Zhiyang Chen , Yousong Zhu , Xin Li , Jinqiao Wang

Diffusion models have achieved impressive results in generative tasks for text-to-video (T2V) synthesis. However, achieving accurate text alignment in T2V generation remains challenging due to the complex temporal dependencies across…

Computer Vision and Pattern Recognition · Computer Science 2025-10-21 Jaemin Kim , Bryan Sangwoo Kim , Jong Chul Ye

The modeling of industrial scenes is essential for simulations in industrial manufacturing. While large language models (LLMs) have shown significant progress in generating general 3D scenes from textual descriptions, generating industrial…

Computation and Language · Computer Science 2025-06-27 Xiao Xia , Dan Zhang , Zibo Liao , Zhenyu Hou , Tianrui Sun , Jing Li , Ling Fu , Yuxiao Dong

Conversation agents fueled by Large Language Models (LLMs) are providing a new way to interact with visual data. While there have been initial attempts for image-based conversation models, this work addresses the under-explored field of…

Computer Vision and Pattern Recognition · Computer Science 2024-06-11 Muhammad Maaz , Hanoona Rasheed , Salman Khan , Fahad Shahbaz Khan

The practical use of text-to-image generation has evolved from simple, monolithic models to complex workflows that combine multiple specialized components. While workflow-based approaches can lead to improved image quality, crafting…

Computer Vision and Pattern Recognition · Computer Science 2024-10-03 Rinon Gal , Adi Haviv , Yuval Alaluf , Amit H. Bermano , Daniel Cohen-Or , Gal Chechik

Text-to-video (T2V) generation is a rapidly growing research area that aims to translate the scenes, objects, and actions within complex video text into a sequence of coherent visual frames. We present FlowZero, a novel framework that…

Computer Vision and Pattern Recognition · Computer Science 2023-11-28 Yu Lu , Linchao Zhu , Hehe Fan , Yi Yang

Current video generation models excel at creating short, realistic clips, but struggle with longer, multi-scene videos. We introduce \texttt{DreamFactory}, an LLM-based framework that tackles this challenge. \texttt{DreamFactory} leverages…

Artificial Intelligence · Computer Science 2024-08-22 Zhifei Xie , Daniel Tang , Dingwei Tan , Jacques Klein , Tegawend F. Bissyand , Saad Ezzini

We present a method for text-driven perpetual view generation -- synthesizing long-term videos of various scenes solely, given an input text prompt describing the scene and camera poses. We introduce a novel framework that generates such…

Computer Vision and Pattern Recognition · Computer Science 2023-05-31 Rafail Fridman , Amit Abecasis , Yoni Kasten , Tali Dekel

Understanding abnormal events in videos is a vital and challenging task that has garnered significant attention in a wide range of applications. Although current video understanding Multi-modal Large Language Models (MLLMs) are capable of…

Computer Vision and Pattern Recognition · Computer Science 2025-11-04 Yingxian Chen , Jiahui Liu , Ruidi Fan , Yanwei Li , Chirui Chang , Shizhen Zhao , Wilton W. T. Fok , Xiaojuan Qi , Yik-Chung Wu

Video Temporal Grounding (VTG) strives to accurately pinpoint event timestamps in a specific video using linguistic queries, significantly impacting downstream tasks like video browsing and editing. Unlike traditional task-specific models,…

Computer Vision and Pattern Recognition · Computer Science 2025-02-04 Yongxin Guo , Jingyu Liu , Mingda Li , Dingxin Cheng , Xiaoying Tang , Dianbo Sui , Qingbin Liu , Xi Chen , Kevin Zhao

Graphics design is important for various applications, including movie production and game design. To create a high-quality scene, designers usually need to spend hours in software like Blender, in which they might need to interleave and…

Computer Vision and Pattern Recognition · Computer Science 2024-08-06 Ian Huang , Guandao Yang , Leonidas Guibas

Recently, the field of text-guided 3D scene generation has garnered significant attention. High-quality generation that aligns with physical realism and high controllability is crucial for practical 3D scene applications. However, existing…

Computer Vision and Pattern Recognition · Computer Science 2026-03-11 Yang Zhou , Zongjin He , Qixuan Li , Chao Wang

The remarkable multimodal capabilities demonstrated by OpenAI's GPT-4 have sparked significant interest in the development of multimodal Large Language Models (LLMs). A primary research objective of such models is to align visual and…

Computer Vision and Pattern Recognition · Computer Science 2023-12-29 Yanda Li , Chi Zhang , Gang Yu , Zhibin Wang , Bin Fu , Guosheng Lin , Chunhua Shen , Ling Chen , Yunchao Wei
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