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Related papers: Enhanced Fine-grained Motion Diffusion for Text-dr…

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Scene synthesis is a challenging problem with several industrial applications. Recently, substantial efforts have been directed to synthesize the scene using human motions, room layouts, or spatial graphs as the input. However, few studies…

Computer Vision and Pattern Recognition · Computer Science 2023-10-25 An Vuong , Minh Nhat Vu , Toan Tien Nguyen , Baoru Huang , Dzung Nguyen , Thieu Vo , Anh Nguyen

Conditional human motion synthesis (HMS) aims to generate human motion sequences that conform to specific conditions. Text and audio represent the two predominant modalities employed as HMS control conditions. While existing research has…

Computer Vision and Pattern Recognition · Computer Science 2024-11-19 Zeyu Ling , Bo Han , Yongkang Wongkan , Han Lin , Mohan Kankanhalli , Weidong Geng

Most text-driven human motion generation methods employ sequential modeling approaches, e.g., transformer, to extract sentence-level text representations automatically and implicitly for human motion synthesis. However, these compact text…

Computer Vision and Pattern Recognition · Computer Science 2023-11-03 Peng Jin , Yang Wu , Yanbo Fan , Zhongqian Sun , Yang Wei , Li Yuan

Despite the growing importance of dental CBCT scans for diagnosis and treatment planning, generating anatomically realistic scans with fine-grained control remains a challenge in medical image synthesis. In this work, we propose a novel…

Computer Vision and Pattern Recognition · Computer Science 2025-08-21 Said Djafar Said , Torkan Gholamalizadeh , Mostafa Mehdipour Ghazi

The body movements accompanying speech aid speakers in expressing their ideas. Co-speech motion generation is one of the important approaches for synthesizing realistic avatars. Due to the intricate correspondence between speech and motion,…

Multimedia · Computer Science 2024-08-28 Sen Wang , Jiangning Zhang , Xin Tan , Zhifeng Xie , Chengjie Wang , Lizhuang Ma

Text-to-video diffusion models have enabled high-quality video synthesis, yet often fail to generate temporally coherent and physically plausible motion. A key reason is the models' insufficient understanding of complex motions that natural…

Computer Vision and Pattern Recognition · Computer Science 2025-10-23 Aritra Bhowmik , Denis Korzhenkov , Cees G. M. Snoek , Amirhossein Habibian , Mohsen Ghafoorian

We present 3DiFACE, a novel method for personalized speech-driven 3D facial animation and editing. While existing methods deterministically predict facial animations from speech, they overlook the inherent one-to-many relationship between…

Computer Vision and Pattern Recognition · Computer Science 2023-12-05 Balamurugan Thambiraja , Sadegh Aliakbarian , Darren Cosker , Justus Thies

This paper introduces a method for realistic kinetic typography that generates user-preferred animatable 'text content'. We draw on recent advances in guided video diffusion models to achieve visually-pleasing text appearances. To do this,…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Seonmi Park , Inhwan Bae , Seunghyun Shin , Hae-Gon Jeon

Along with the explosion of large language models, improvements in speech synthesis, advancements in hardware, and the evolution of computer graphics, the current bottleneck in creating digital humans lies in generating character movements…

Human-Computer Interaction · Computer Science 2026-01-30 Thanh Hoang-Minh

This study introduces a text-conditioned approach to generating drumbeats with Latent Diffusion Models (LDMs). It uses informative conditioning text extracted from training data filenames. By pretraining a text and drumbeat encoder through…

Sound · Computer Science 2024-08-07 Pushkar Jajoria , James McDermott

In this work, we propose TextIM, a novel framework for synthesizing TEXT-driven human Interactive Motions, with a focus on the precise alignment of part-level semantics. Existing methods often overlook the critical roles of interactive body…

Computer Vision and Pattern Recognition · Computer Science 2024-08-07 Siyuan Fan , Bo Du , Xiantao Cai , Bo Peng , Longling Sun

By decomposing the image formation process into a sequential application of denoising autoencoders, diffusion models (DMs) achieve state-of-the-art synthesis results on image data and beyond. Additionally, their formulation allows for a…

Computer Vision and Pattern Recognition · Computer Science 2022-04-14 Robin Rombach , Andreas Blattmann , Dominik Lorenz , Patrick Esser , Björn Ommer

Recent advances in conditional diffusion models have shown promise for generating realistic TalkingFace videos, yet challenges persist in achieving consistent head movement, synchronized facial expressions, and accurate lip synchronization…

Computer Vision and Pattern Recognition · Computer Science 2025-02-14 Fei Shen , Cong Wang , Junyao Gao , Qin Guo , Jisheng Dang , Jinhui Tang , Tat-Seng Chua

Match-cuts are powerful cinematic tools that create seamless transitions between scenes, delivering strong visual and metaphorical connections. However, crafting match-cuts is a challenging, resource-intensive process requiring deliberate…

Computer Vision and Pattern Recognition · Computer Science 2024-12-02 Alejandro Pardo , Fabio Pizzati , Tong Zhang , Alexander Pondaven , Philip Torr , Juan Camilo Perez , Bernard Ghanem

Creating a vivid video from the event or scenario in our imagination is a truly fascinating experience. Recent advancements in text-to-video synthesis have unveiled the potential to achieve this with prompts only. While text is convenient…

Computer Vision and Pattern Recognition · Computer Science 2023-06-02 Jinbo Xing , Menghan Xia , Yuxin Liu , Yuechen Zhang , Yong Zhang , Yingqing He , Hanyuan Liu , Haoxin Chen , Xiaodong Cun , Xintao Wang , Ying Shan , Tien-Tsin Wong

Current text recognition systems, including those for handwritten scripts and scene text, have relied heavily on image synthesis and augmentation, since it is difficult to realize real-world complexity and diversity through collecting and…

Computer Vision and Pattern Recognition · Computer Science 2023-06-21 Yuanzhi Zhu , Zhaohai Li , Tianwei Wang , Mengchao He , Cong Yao

Generating human motion from textual descriptions is a challenging task. Existing methods either struggle with physical credibility or are limited by the complexities of physics simulations. In this paper, we present \emph{ReinDiffuse} that…

Computer Vision and Pattern Recognition · Computer Science 2024-10-16 Gaoge Han , Mingjiang Liang , Jinglei Tang , Yongkang Cheng , Wei Liu , Shaoli Huang

Video generation primarily aims to model authentic and customized motion across frames, making understanding and controlling the motion a crucial topic. Most diffusion-based studies on video motion focus on motion customization with…

Computer Vision and Pattern Recognition · Computer Science 2024-11-13 Zeqi Xiao , Yifan Zhou , Shuai Yang , Xingang Pan

Designing effective camera trajectories in virtual 3D environments is a challenging task even for experienced animators. Despite an elaborate film grammar, forged through years of experience, that enables the specification of camera motions…

Graphics · Computer Science 2024-02-27 Hongda Jiang , Xi Wang , Marc Christie , Libin Liu , Baoquan Chen

Image generation has recently seen tremendous advances, with diffusion models allowing to synthesize convincing images for a large variety of text prompts. In this article, we propose DiffEdit, a method to take advantage of text-conditioned…

Computer Vision and Pattern Recognition · Computer Science 2022-10-21 Guillaume Couairon , Jakob Verbeek , Holger Schwenk , Matthieu Cord