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While users tend to perceive instructional videos as an experience rather than a lesson with a set of instructions, instructional videos are more effective and appealing than textual user manuals and eliminate the ambiguity in text-based…

Human-Computer Interaction · Computer Science 2023-11-22 Songsong Liu , Shu Wang , Kun Sun

Existing multimodal generative models fall short as qualified design copilots, as they often struggle to generate imaginative outputs once instructions are less detailed or lack the ability to maintain consistency with the provided…

Computer Vision and Pattern Recognition · Computer Science 2025-03-11 Zhipeng Huang , Shaobin Zhuang , Canmiao Fu , Binxin Yang , Ying Zhang , Chong Sun , Zhizheng Zhang , Yali Wang , Chen Li , Zheng-Jun Zha

The objective of this work is to manipulate visual timelines (e.g. a video) through natural language instructions, making complex timeline editing tasks accessible to non-expert or potentially even disabled users. We call this task…

Computer Vision and Pattern Recognition · Computer Science 2024-11-20 Alejandro Pardo , Jui-Hsien Wang , Bernard Ghanem , Josef Sivic , Bryan Russell , Fabian Caba Heilbron

Recent advances in diffusion models bring new vitality to visual content creation. However, current text-to-video generation models still face significant challenges such as high training costs, substantial data requirements, and…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Sicong Feng , Jielong Yang , Li Peng

Large-scale video generative models have recently demonstrated strong visual capabilities, enabling the prediction of future frames that adhere to the logical and physical cues in the current observation. In this work, we investigate…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Gongfan Fang , Xinyin Ma , Xinchao Wang

Image-to-video (I2V) generation seeks to produce realistic motion sequences from a single reference image. Although recent methods exhibit strong temporal consistency, they often struggle when dealing with complex, non-repetitive human…

Computer Vision and Pattern Recognition · Computer Science 2025-07-01 Ashkan Taghipour , Morteza Ghahremani , Mohammed Bennamoun , Farid Boussaid , Aref Miri Rekavandi , Zinuo Li , Qiuhong Ke , Hamid Laga

Video generation is a challenging yet pivotal task in various industries, such as gaming, e-commerce, and advertising. One significant unresolved aspect within T2V is the effective visualization of text within generated videos. Despite the…

Computer Vision and Pattern Recognition · Computer Science 2024-06-26 Lin Liu , Quande Liu , Shengju Qian , Yuan Zhou , Wengang Zhou , Houqiang Li , Lingxi Xie , Qi Tian

We propose a novel task of text-controlled human object interaction generation in 3D scenes with movable objects. Existing human-scene interaction datasets suffer from insufficient interaction categories and typically only consider…

Computer Vision and Pattern Recognition · Computer Science 2025-09-30 Xinhao Cai , Minghang Zheng , Xin Jin , Yang Liu

Modern game development faces significant challenges in creativity and cost due to predetermined content in traditional game engines. Recent breakthroughs in video generation models, capable of synthesizing realistic and interactive virtual…

Computer Vision and Pattern Recognition · Computer Science 2025-05-30 Jiwen Yu , Yiran Qin , Haoxuan Che , Quande Liu , Xintao Wang , Pengfei Wan , Di Zhang , Xihui Liu

Generative videos have the potential to revolutionize game development by autonomously creating new content. In this paper, we present GameFactory, a framework for action-controlled scene-generalizable game video generation. We first…

Computer Vision and Pattern Recognition · Computer Science 2025-10-31 Jiwen Yu , Yiran Qin , Xintao Wang , Pengfei Wan , Di Zhang , Xihui Liu

Yume aims to use images, text, or videos to create an interactive, realistic, and dynamic world, which allows exploration and control using peripheral devices or neural signals. In this report, we present a preview version of \method, which…

Computer Vision and Pattern Recognition · Computer Science 2025-07-24 Xiaofeng Mao , Shaoheng Lin , Zhen Li , Chuanhao Li , Wenshuo Peng , Tong He , Jiangmiao Pang , Mingmin Chi , Yu Qiao , Kaipeng Zhang

Unlike static and rigid user interfaces, generative and malleable user interfaces offer the potential to respond to diverse users' goals and tasks. However, current approaches primarily rely on generating code, making it difficult for…

Human-Computer Interaction · Computer Science 2025-03-07 Yining Cao , Peiling Jiang , Haijun Xia

While recent generative models advance pixel-space video synthesis, they remain limited in producing professional educational videos, which demand disciplinary knowledge, precise visual structures, and coherent transitions, limiting their…

Computer Vision and Pattern Recognition · Computer Science 2025-10-02 Yanzhe Chen , Kevin Qinghong Lin , Mike Zheng Shou

With the rise of short video platforms represented by TikTok, the trend of users expressing their creativity through photos and videos has increased dramatically. However, ordinary users lack the professional skills to produce high-quality…

Computer Vision and Pattern Recognition · Computer Science 2024-02-27 Sixiao Zheng , Jingyang Huo , Yu Wang , Yanwei Fu

Generating videos for visual storytelling can be a tedious and complex process that typically requires either live-action filming or graphics animation rendering. To bypass these challenges, our key idea is to utilize the abundance of…

Computer Vision and Pattern Recognition · Computer Science 2023-07-14 Yingqing He , Menghan Xia , Haoxin Chen , Xiaodong Cun , Yuan Gong , Jinbo Xing , Yong Zhang , Xintao Wang , Chao Weng , Ying Shan , Qifeng Chen

Synthesizing motion-rich and temporally consistent videos remains a challenge in artificial intelligence, especially when dealing with extended durations. Existing text-to-video (T2V) models commonly employ spatial cross-attention for text…

Computer Vision and Pattern Recognition · Computer Science 2025-08-18 Jiasong Feng , Ao Ma , Jing Wang , Ke Cao , Zhanjie Zhang

Creation of images using generative adversarial networks has been widely adapted into multi-modal regime with the advent of multi-modal representation models pre-trained on large corpus. Various modalities sharing a common representation…

Sound · Computer Science 2022-06-10 Yoonjeon Kim , Joel Jang , Sumin Shin

While text-to-video diffusion models have made significant strides, many still face challenges in generating videos with temporal consistency. Within diffusion frameworks, guidance techniques have proven effective in enhancing output…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Hyelin Nam , Jaemin Kim , Dohun Lee , Jong Chul Ye

Recent advances in generative world models have enabled remarkable progress in creating open-ended game environments, evolving from static scene synthesis toward dynamic, interactive simulation. However, current approaches remain limited by…

Computer Vision and Pattern Recognition · Computer Science 2026-02-11 Junshu Tang , Jiacheng Liu , Jiaqi Li , Longhuang Wu , Haoyu Yang , Penghao Zhao , Siruis Gong , Xiang Yuan , Shuai Shao , Linfeng Zhang , Qinglin Lu

Users often take notes for instructional videos to access key knowledge later without revisiting long videos. Automated note generation tools enable users to obtain informative notes efficiently. However, notes generated by existing…

Human-Computer Interaction · Computer Science 2025-08-21 Running Zhao , Zhihan Jiang , Xinchen Zhang , Chirui Chang , Handi Chen , Weipeng Deng , Luyao Jin , Xiaojuan Qi , Xun Qian , Edith C. H. Ngai