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The emergence of text-driven motion synthesis technique provides animators with great potential to create efficiently. However, in most cases, textual expressions only contain general and qualitative motion descriptions, while lack fine…

Computer Vision and Pattern Recognition · Computer Science 2023-12-27 Dong Wei , Xiaoning Sun , Huaijiang Sun , Bin Li , Shengxiang Hu , Weiqing Li , Jianfeng Lu

Diffusion generative models have recently become a powerful technique for creating and modifying high-quality, coherent video content. This survey provides a comprehensive overview of the critical components of diffusion models for video…

Computer Vision and Pattern Recognition · Computer Science 2024-11-19 Andrew Melnik , Michal Ljubljanac , Cong Lu , Qi Yan , Weiming Ren , Helge Ritter

While modern diffusion models excel at generating high-quality and diverse images, they still struggle with high-fidelity compositional and multimodal control, particularly when users simultaneously specify text prompts, subject references,…

Computer Vision and Pattern Recognition · Computer Science 2025-11-27 Yusuf Dalva , Guocheng Gordon Qian , Maya Goldenberg , Tsai-Shien Chen , Kfir Aberman , Sergey Tulyakov , Pinar Yanardag , Kuan-Chieh Jackson Wang

In Text-to-Image (T2I) generation, the complexity of entities and their intricate interactions pose a significant challenge for T2I method based on diffusion model: how to effectively control entity and their interactions to produce…

Computer Vision and Pattern Recognition · Computer Science 2025-08-26 Mingyue Yang , Dianxi Shi , Jialu Zhou , Xinyu Wei , Leqian Li , Shaowu Yang , Chunping Qiu

We present WorldCanvas, a framework for promptable world events that enables rich, user-directed simulation by combining text, trajectories, and reference images. Unlike text-only approaches and existing trajectory-controlled image-to-video…

Computer Vision and Pattern Recognition · Computer Science 2025-12-19 Hanlin Wang , Hao Ouyang , Qiuyu Wang , Yue Yu , Yihao Meng , Wen Wang , Ka Leong Cheng , Shuailei Ma , Qingyan Bai , Yixuan Li , Cheng Chen , Yanhong Zeng , Xing Zhu , Yujun Shen , Qifeng Chen

We present Yan, a foundational framework for interactive video generation, covering the entire pipeline from simulation and generation to editing. Specifically, Yan comprises three core modules. AAA-level Simulation: We design a…

Computer Vision and Pattern Recognition · Computer Science 2025-08-15 Deheng Ye , Fangyun Zhou , Jiacheng Lv , Jianqi Ma , Jun Zhang , Junyan Lv , Junyou Li , Minwen Deng , Mingyu Yang , Qiang Fu , Wei Yang , Wenkai Lv , Yangbin Yu , Yewen Wang , Yonghang Guan , Zhihao Hu , Zhongbin Fang , Zhongqian Sun

For recent diffusion-based generative models, maintaining consistent content across a series of generated images, especially those containing subjects and complex details, presents a significant challenge. In this paper, we propose a new…

Computer Vision and Pattern Recognition · Computer Science 2024-05-03 Yupeng Zhou , Daquan Zhou , Ming-Ming Cheng , Jiashi Feng , Qibin Hou

Diffusion-based methods have achieved remarkable achievements in 2D image or 3D object generation, however, the generation of 3D scenes and even $360^{\circ}$ images remains constrained, due to the limited number of scene datasets, the…

Computer Vision and Pattern Recognition · Computer Science 2024-11-01 Weicai Ye , Chenhao Ji , Zheng Chen , Junyao Gao , Xiaoshui Huang , Song-Hai Zhang , Wanli Ouyang , Tong He , Cairong Zhao , Guofeng Zhang

Text-to-Image (T2I) generation methods based on diffusion model have garnered significant attention in the last few years. Although these image synthesis methods produce visually appealing results, they frequently exhibit spelling errors…

Computer Vision and Pattern Recognition · Computer Science 2023-12-27 Yiming Zhao , Zhouhui Lian

Scaling generative inverse and forward rendering to real-world scenarios is bottlenecked by the limited realism and temporal coherence of existing synthetic datasets. To bridge this persistent domain gap, we introduce a large-scale, dynamic…

Computer Vision and Pattern Recognition · Computer Science 2026-04-03 Zheng-Hui Huang , Zhixiang Wang , Jiaming Tan , Ruihan Yu , Yidan Zhang , Bo Zheng , Yu-Lun Liu , Yung-Yu Chuang , Kaipeng Zhang

Despite remarkable achievements in video synthesis, achieving granular control over complex dynamics, such as nuanced movement among multiple interacting objects, still presents a significant hurdle for dynamic world modeling, compounded by…

Computer Vision and Pattern Recognition · Computer Science 2024-03-21 Pengxiang Li , Kai Chen , Zhili Liu , Ruiyuan Gao , Lanqing Hong , Guo Zhou , Hua Yao , Dit-Yan Yeung , Huchuan Lu , Xu Jia

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

Text-driven content creation has evolved to be a transformative technique that revolutionizes creativity. Here we study the task of text-driven human video generation, where a video sequence is synthesized from texts describing the…

Computer Vision and Pattern Recognition · Computer Science 2023-04-18 Yuming Jiang , Shuai Yang , Tong Liang Koh , Wayne Wu , Chen Change Loy , Ziwei Liu

The advent of text-driven 360-degree panorama generation, enabling the synthesis of 360-degree panoramic images directly from textual descriptions, marks a transformative advancement in immersive visual content creation. This innovation…

Computer Vision and Pattern Recognition · Computer Science 2025-11-06 Hai Wang , Xiaoyu Xiang , Weihao Xia , Jing-Hao Xue

Recent advancements in diffusion models have significantly advanced text-to-image generation, yet global text prompts alone remain insufficient for achieving fine-grained control over individual entities within an image. To address this…

Computer Vision and Pattern Recognition · Computer Science 2025-01-31 Hong Zhang , Zhongjie Duan , Xingjun Wang , Yingda Chen , Yu Zhang

We introduce animated stickers, a video diffusion model which generates an animation conditioned on a text prompt and static sticker image. Our model is built on top of the state-of-the-art Emu text-to-image model, with the addition of…

Currently, personalized image generation methods mostly require considerable time to finetune and often overfit the concept resulting in generated images that are similar to custom concepts but difficult to edit by prompts. We propose an…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Yuxuan Zhang , Yiren Song , Jinpeng Yu , Han Pan , Zhongliang Jing

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

Diffusion generative models have recently greatly improved the power of text-conditioned image generation. Existing image generation models mainly include text conditional diffusion model and cross-modal guided diffusion model, which are…

Computer Vision and Pattern Recognition · Computer Science 2022-11-04 Wei Li , Xue Xu , Xinyan Xiao , Jiachen Liu , Hu Yang , Guohao Li , Zhanpeng Wang , Zhifan Feng , Qiaoqiao She , Yajuan Lyu , Hua Wu

Recent advances in world models have greatly enhanced interactive environment simulation. Existing methods mainly fall into two categories: (1) static world generation models, which construct 3D environments without active agents, and (2)…

Computer Vision and Pattern Recognition · Computer Science 2025-12-22 Yitong Wang , Fangyun Wei , Hongyang Zhang , Bo Dai , Yan Lu