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Text-to-video generation aims to produce a video based on a given prompt. Recently, several commercial video models have been able to generate plausible videos with minimal noise, excellent details, and high aesthetic scores. However, these…

Computer Vision and Pattern Recognition · Computer Science 2024-01-18 Haoxin Chen , Yong Zhang , Xiaodong Cun , Menghan Xia , Xintao Wang , Chao Weng , Ying Shan

Generating videos from text has proven to be a significant challenge for existing generative models. We tackle this problem by training a conditional generative model to extract both static and dynamic information from text. This is…

Multimedia · Computer Science 2017-10-03 Yitong Li , Martin Renqiang Min , Dinghan Shen , David Carlson , Lawrence Carin

Can visual artworks created using generative visual algorithms inspire human creativity in storytelling? We asked writers to write creative stories from a starting prompt, and provided them with visuals created by generative AI models from…

Human-Computer Interaction · Computer Science 2021-10-29 Safinah Ali , Devi Parikh

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

Human video generation is becoming an increasingly important task with broad applications in graphics, entertainment, and embodied AI. Despite the rapid progress of video diffusion models (VDMs), their use for general-purpose human video…

Computer Vision and Pattern Recognition · Computer Science 2025-10-07 Hyelin Nam , Hyojun Go , Byeongjun Park , Byung-Hoon Kim , Hyungjin Chung

This paper investigates a novel task of talking face video generation solely from speeches. The speech-to-video generation technique can spark interesting applications in entertainment, customer service, and human-computer-interaction…

Sound · Computer Science 2021-07-15 Shijing Si , Jianzong Wang , Xiaoyang Qu , Ning Cheng , Wenqi Wei , Xinghua Zhu , Jing Xiao

Video generation is experiencing rapid growth, driven by advances in diffusion models and the development of better and larger datasets. However, producing high-quality videos remains challenging due to the high-dimensional data and the…

Computer Vision and Pattern Recognition · Computer Science 2025-04-10 Elia Peruzzo , Dejia Xu , Xingqian Xu , Humphrey Shi , Nicu Sebe

Unified multimodal models integrating visual understanding and generation face a fundamental challenge: visual generation incurs substantially higher computational costs than understanding, particularly for video. This imbalance motivates…

Computer Vision and Pattern Recognition · Computer Science 2026-04-10 Luozheng Qin , Jia Gong , Qian Qiao , Tianjiao Li , Li Xu , Haoyu Pan , Chao Qu , Zhiyu Tan , Hao Li

Diffusion and flow matching models have unlocked unprecedented capabilities for creative content creation, such as interactive image and streaming video generation. The growing demand for higher resolutions, frame rates, and context…

Computer Vision and Pattern Recognition · Computer Science 2026-03-25 Brian Chao , Lior Yariv , Howard Xiao , Gordon Wetzstein

We introduce VividDream, a method for generating explorable 4D scenes with ambient dynamics from a single input image or text prompt. VividDream first expands an input image into a static 3D point cloud through iterative inpainting and…

Computer Vision and Pattern Recognition · Computer Science 2024-05-31 Yao-Chih Lee , Yi-Ting Chen , Andrew Wang , Ting-Hsuan Liao , Brandon Y. Feng , Jia-Bin Huang

Creating a cohesive, high-quality, relevant, media story is a challenge that news media editors face on a daily basis. This challenge is aggravated by the flood of highly relevant information that is constantly pouring onto the newsroom. To…

Multimedia · Computer Science 2021-10-14 Gonçalo Marcelino , David Semedo , André Mourão , Saverio Blasi , Marta Mrak , João Magalhães

Recent video generation models have shown promising results in producing high-quality video clips lasting several seconds. However, these models face challenges in generating long sequences that convey clear and informative events, limiting…

Computer Vision and Pattern Recognition · Computer Science 2025-06-10 Junfei Xiao , Feng Cheng , Lu Qi , Liangke Gui , Jiepeng Cen , Zhibei Ma , Alan Yuille , Lu Jiang

How does audio describe the world around us? In this work, we propose a method for generating images of visual scenes from diverse in-the-wild sounds. This cross-modal generation task is challenging due to the significant information gap…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Kim Sung-Bin , Arda Senocak , Hyunwoo Ha , Tae-Hyun Oh

Automatically describing video content with text description is challenging but important task, which has been attracting a lot of attention in computer vision community. Previous works mainly strive for the accuracy of the generated…

Computer Vision and Pattern Recognition · Computer Science 2021-06-16 Huanhou Xiao , Jinglun Shi

We present Imagen Video, a text-conditional video generation system based on a cascade of video diffusion models. Given a text prompt, Imagen Video generates high definition videos using a base video generation model and a sequence of…

Computer Vision and Pattern Recognition · Computer Science 2022-10-06 Jonathan Ho , William Chan , Chitwan Saharia , Jay Whang , Ruiqi Gao , Alexey Gritsenko , Diederik P. Kingma , Ben Poole , Mohammad Norouzi , David J. Fleet , Tim Salimans

We introduce Vid-CamEdit, a novel framework for video camera trajectory editing, enabling the re-synthesis of monocular videos along user-defined camera paths. This task is challenging due to its ill-posed nature and the limited multi-view…

Computer Vision and Pattern Recognition · Computer Science 2025-06-17 Junyoung Seo , Jisang Han , Jaewoo Jung , Siyoon Jin , Joungbin Lee , Takuya Narihira , Kazumi Fukuda , Takashi Shibuya , Donghoon Ahn , Shoukang Hu , Seungryong Kim , Yuki Mitsufuji

We introduce $\textit{InteractiveVideo}$, a user-centric framework for video generation. Different from traditional generative approaches that operate based on user-provided images or text, our framework is designed for dynamic interaction,…

Computer Vision and Pattern Recognition · Computer Science 2024-02-06 Yiyuan Zhang , Yuhao Kang , Zhixin Zhang , Xiaohan Ding , Sanyuan Zhao , Xiangyu Yue

Audience feedback is crucial for refining video content, yet it typically comes after publication, limiting creators' ability to make timely adjustments. To bridge this gap, we introduce SimTube, a generative AI system designed to simulate…

Human-Computer Interaction · Computer Science 2024-11-19 Yu-Kai Hung , Yun-Chien Huang , Ting-Yu Su , Yen-Ting Lin , Lung-Pan Cheng , Bryan Wang , Shao-Hua Sun

Recent years have seen a significant increase in video content creation and consumption. Crafting engaging content requires the careful curation of both visual and audio elements. While visual cue curation, through techniques like optimal…

Computer Vision and Pattern Recognition · Computer Science 2025-05-20 Chao Huang , Ruohan Gao , J. M. F. Tsang , Jan Kurcius , Cagdas Bilen , Chenliang Xu , Anurag Kumar , Sanjeel Parekh

Recently, breakthroughs in video modeling have allowed for controllable camera trajectories in generated videos. However, these methods cannot be directly applied to user-provided videos that are not generated by a video model. In this…

Computer Vision and Pattern Recognition · Computer Science 2024-11-08 David Junhao Zhang , Roni Paiss , Shiran Zada , Nikhil Karnad , David E. Jacobs , Yael Pritch , Inbar Mosseri , Mike Zheng Shou , Neal Wadhwa , Nataniel Ruiz
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