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Creating high-dynamic videos such as motion-rich actions and sophisticated visual effects poses a significant challenge in the field of artificial intelligence. Unfortunately, current state-of-the-art video generation methods, primarily…

Computer Vision and Pattern Recognition · Computer Science 2023-11-21 Yan Zeng , Guoqiang Wei , Jiani Zheng , Jiaxin Zou , Yang Wei , Yuchen Zhang , Hang Li

Generating animated 3D objects is at the heart of many applications, yet most advanced works are typically difficult to apply in practice because of their limited setup, their long runtime, or their limited quality. We introduce ActionMesh,…

Computer Vision and Pattern Recognition · Computer Science 2026-04-02 Remy Sabathier , David Novotny , Niloy J. Mitra , Tom Monnier

Recent text-to-video generation approaches rely on computationally heavy training and require large-scale video datasets. In this paper, we introduce a new task of zero-shot text-to-video generation and propose a low-cost approach (without…

Computer Vision and Pattern Recognition · Computer Science 2023-03-24 Levon Khachatryan , Andranik Movsisyan , Vahram Tadevosyan , Roberto Henschel , Zhangyang Wang , Shant Navasardyan , Humphrey Shi

Large text-guided diffusion models, such as DALLE-2, are able to generate stunning photorealistic images given natural language descriptions. While such models are highly flexible, they struggle to understand the composition of certain…

Computer Vision and Pattern Recognition · Computer Science 2023-01-18 Nan Liu , Shuang Li , Yilun Du , Antonio Torralba , Joshua B. Tenenbaum

Controlling the behavior of language models (LMs) without re-training is a major open problem in natural language generation. While recent works have demonstrated successes on controlling simple sentence attributes (e.g., sentiment), there…

Computation and Language · Computer Science 2022-05-31 Xiang Lisa Li , John Thickstun , Ishaan Gulrajani , Percy Liang , Tatsunori B. Hashimoto

Recent approaches have demonstrated the promise of using diffusion models to generate interactive and explorable worlds. However, most of these methods face critical challenges such as excessively large parameter sizes, reliance on lengthy…

Computer Vision and Pattern Recognition · Computer Science 2025-12-29 Xiaofeng Mao , Zhen Li , Chuanhao Li , Xiaojie Xu , Kaining Ying , Tong He , Jiangmiao Pang , Yu Qiao , Kaipeng Zhang

Recent diffusion-based methods for material transfer rely on image fine-tuning or complex architectures with assistive networks, but face challenges including text dependency, extra computational costs, and feature misalignment. To address…

Computer Vision and Pattern Recognition · Computer Science 2026-05-18 Nisha Huang , Henglin Liu , Yizhou Lin , Kaer Huang , Chubin Chen , Jie Guo , Tong-Yee Lee , Xiu Li

Diffusion models have achieved remarkable progress in video generation, but their controllability remains a major limitation. Key scene factors such as layout, lighting, and camera trajectory are often entangled or only weakly modeled,…

Computer Vision and Pattern Recognition · Computer Science 2026-04-10 Ziqi Cai , Taoyu Yang , Zheng Chang , Si Li , Han Jiang , Shuchen Weng , Boxin Shi

Synthesizing human motions in 3D environments, particularly those with complex activities such as locomotion, hand-reaching, and human-object interaction, presents substantial demands for user-defined waypoints and stage transitions. These…

Computer Vision and Pattern Recognition · Computer Science 2024-10-10 Nan Jiang , Zimo He , Zi Wang , Hongjie Li , Yixin Chen , Siyuan Huang , Yixin Zhu

Recent advancements in diffusion models have significantly improved the realism and generalizability of character-driven animation, enabling the synthesis of high-quality motion from just a single RGB image and a set of driving poses.…

Computer Vision and Pattern Recognition · Computer Science 2025-12-02 Alireza Javanmardi , Pragati Jaiswal , Tewodros Amberbir Habtegebrial , Christen Millerdurai , Shaoxiang Wang , Alain Pagani , Didier Stricker

There has been tremendous progress in large-scale text-to-image synthesis driven by diffusion models enabling versatile downstream applications such as 3D object synthesis from texts, image editing, and customized generation. We present a…

Computer Vision and Pattern Recognition · Computer Science 2023-04-05 Ting-Hsuan Liao , Songwei Ge , Yiran Xu , Yao-Chih Lee , Badour AlBahar , Jia-Bin Huang

Recently, 3D generation methods have shown their powerful ability to automate 3D model creation. However, most 3D generation methods only rely on an input image or a text prompt to generate a 3D model, which lacks the control of each…

Computer Vision and Pattern Recognition · Computer Science 2025-07-08 Peng Li , Suizhi Ma , Jialiang Chen , Yuan Liu , Congyi Zhang , Wei Xue , Wenhan Luo , Alla Sheffer , Wenping Wang , Yike Guo

This paper does not describe a new method; instead, it provides a thorough exploration of an important yet understudied design space related to recent advances in text-to-image synthesis -- specifically, the deep fusion of large language…

Computer Vision and Pattern Recognition · Computer Science 2025-05-16 Bingda Tang , Boyang Zheng , Xichen Pan , Sayak Paul , Saining Xie

Given the steep learning curve of professional 3D software and the time-consuming process of managing large 3D assets, language-guided 3D scene editing has significant potential in fields such as virtual reality, augmented reality, and…

Despite the ability of existing large-scale text-to-image (T2I) models to generate high-quality images from detailed textual descriptions, they often lack the ability to precisely edit the generated or real images. In this paper, we propose…

Computer Vision and Pattern Recognition · Computer Science 2023-11-21 Chong Mou , Xintao Wang , Jiechong Song , Ying Shan , Jian Zhang

Diffusion-based methods can generate realistic images and videos, but they struggle to edit existing objects in a video while preserving their appearance over time. This prevents diffusion models from being applied to natural video editing…

Computer Vision and Pattern Recognition · Computer Science 2023-08-21 Wenhao Chai , Xun Guo , Gaoang Wang , Yan Lu

The field of photorealistic 3D avatar reconstruction and generation has garnered significant attention in recent years; however, animating such avatars remains challenging. Recent advances in diffusion models have notably enhanced the…

Text driven diffusion models have shown remarkable capabilities in editing images. However, when editing 3D scenes, existing works mostly rely on training a NeRF for 3D editing. Recent NeRF editing methods leverages edit operations by…

Computer Vision and Pattern Recognition · Computer Science 2024-12-18 Vivek Madhavaram , Shivangana Rawat , Chaitanya Devaguptapu , Charu Sharma , Manohar Kaul

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

Diffusion models are the current state-of-the-art in image generation, synthesizing high-quality images by breaking down the generation process into many fine-grained denoising steps. Despite their good performance, diffusion models are…

Computer Vision and Pattern Recognition · Computer Science 2023-10-31 Noam Elata , Bahjat Kawar , Tomer Michaeli , Michael Elad