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The task of talking head generation is to synthesize a lip synchronized talking head video by inputting an arbitrary face image and audio clips. Most existing methods ignore the local driving information of the mouth muscles. In this paper,…

Computer Vision and Pattern Recognition · Computer Science 2021-10-20 Sen Chen , Zhilei Liu , Jiaxing Liu , Zhengxiang Yan , Longbiao Wang

Speech-driven three-dimensional (3D) facial animation synthesis aims to build a mapping from one-dimensional (1D) speech signals to time-varying 3D facial motion signals. Current methods still face challenges in maintaining lip-sync…

Computer Vision and Pattern Recognition · Computer Science 2026-04-06 Bin Liu , Zhixiang Xiong , Zhifen He , Bo Li

Open-vocabulary panoptic reconstruction is a challenging task for simultaneous scene reconstruction and understanding. Recently, methods have been proposed for 3D scene understanding based on Gaussian splatting. However, these methods are…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Yuxuan Xie , Xuan Yu , Changjian Jiang , Sitong Mao , Shunbo Zhou , Rui Fan , Rong Xiong , Yue Wang

Visuomotor policies learned from teleoperated demonstrations face challenges such as lengthy data collection, high costs, and limited data diversity. Existing approaches address these issues by augmenting image observations in RGB space or…

Robotics · Computer Science 2025-04-18 Sizhe Yang , Wenye Yu , Jia Zeng , Jun Lv , Kerui Ren , Cewu Lu , Dahua Lin , Jiangmiao Pang

Most earlier researches on talking face generation have focused on the synchronization of lip motion and speech content. However, head pose and facial emotions are equally important characteristics of natural faces. While audio-driven…

Computer Vision and Pattern Recognition · Computer Science 2024-11-05 Changpeng Cai , Guinan Guo , Jiao Li , Junhao Su , Fei Shen , Chenghao He , Jing Xiao , Yuanxu Chen , Lei Dai , Feiyu Zhu

The one-shot talking-head generation learns to synthesize a talking-head video with one source portrait image under the driving of same or different identity video. Usually these methods require plane-based pixel transformations via Jacobin…

Computer Vision and Pattern Recognition · Computer Science 2024-03-26 Luchuan Song , Pinxin Liu , Guojun Yin , Chenliang Xu

State-of-the-art novel view synthesis methods achieve impressive results for multi-view captures of static 3D scenes. However, the reconstructed scenes still lack "liveliness," a key component for creating engaging 3D experiences. Recently,…

Computer Vision and Pattern Recognition · Computer Science 2025-03-10 Thomas Wimmer , Michael Oechsle , Michael Niemeyer , Federico Tombari

Gaussian Splatting has achieved remarkable progress in multi-view surface reconstruction, yet it exhibits notable degradation when only few views are available. Although recent efforts alleviate this issue by enhancing multi-view…

Computer Vision and Pattern Recognition · Computer Science 2026-05-13 Jimin Tang , Wenyuan Zhang , Junsheng Zhou , Zian Huang , Kanle Shi , Shenkun Xu , Yu-Shen Liu , Zhizhong Han

Language-driven 3D Gaussian Splatting (3DGS) editing provides a more convenient approach for modifying complex scenes in VR/AR. Standard pipelines typically adopt a two-stage strategy: first editing multiple 2D views, and then optimizing…

Computer Vision and Pattern Recognition · Computer Science 2026-05-01 Yanhui Chen , Jiahong Li , Jingchao Wang , Junyi Lin , Zixin Zeng , Yang Shi

Creating photorealistic 3D head avatars from limited input has become increasingly important for applications in virtual reality, telepresence, and digital entertainment. While recent advances like neural rendering and 3D Gaussian splatting…

Graphics · Computer Science 2026-03-12 Chen Guo , Zhuo Su , Liao Wang , Jian Wang , Shuang Li , Xu Chang , Zhaohu Li , Yang Zhao , Guidong Wang , Yebin Liu , Ruqi Huang

Language-guided 3D scene understanding is important for advancing applications in robotics, AR/VR, and human-computer interaction, enabling models to comprehend and interact with 3D environments through natural language. While 2D…

Computer Vision and Pattern Recognition · Computer Science 2025-08-05 Anh Thai , Songyou Peng , Kyle Genova , Leonidas Guibas , Thomas Funkhouser

The modeling and manipulation of 3D scenes captured from the real world are pivotal in various applications, attracting growing research interest. While previous works on editing have achieved interesting results through manipulating 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-08-15 Guan Luo , Tian-Xing Xu , Ying-Tian Liu , Xiao-Xiong Fan , Fang-Lue Zhang , Song-Hai Zhang

3D Gaussian Splatting (3DGS) has emerged as a leading approach for high-quality novel view synthesis, with numerous variants extending its applicability to a broad spectrum of 3D and 4D scene reconstruction tasks. Despite its success, the…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Yiming Wang , Shaofei Wang , Marko Mihajlovic , Siyu Tang

Generalizable 3D Gaussian Splatting reconstruction showcases advanced Image-to-3D content creation but requires substantial computational resources and large datasets, posing challenges to training models from scratch. Current methods…

Computer Vision and Pattern Recognition · Computer Science 2026-01-05 Xiufeng Huang , Ka Chun Cheung , Runmin Cong , Simon See , Renjie Wan

Audio-driven talking head generation is advancing from 2D to 3D content. Notably, Neural Radiance Field (NeRF) is in the spotlight as a means to synthesize high-quality 3D talking head outputs. Unfortunately, this NeRF-based approach…

Computer Vision and Pattern Recognition · Computer Science 2024-05-13 Gihoon Kim , Kwanggyoon Seo , Sihun Cha , Junyong Noh

Researchers have shown a growing interest in Audio-driven Talking Head Generation. The primary challenge in talking head generation is achieving audio-visual coherence between the lips and the audio, known as lip synchronization. This paper…

Sound · Computer Science 2026-02-03 Zhipeng Chen , Xinheng Wang , Lun Xie , Haijie Yuan , Hang Pan

Creating high-fidelity, animatable 3D talking heads is crucial for immersive applications, yet often hindered by the prevalence of low-quality image or video sources, which yield poor 3D reconstructions. In this paper, we introduce…

Computer Vision and Pattern Recognition · Computer Science 2026-02-09 Ding-Jiun Huang , Yuanhao Wang , Shao-Ji Yuan , Albert Mosella-Montoro , Francisco Vicente Carrasco , Cheng Zhang , Fernando De la Torre

Audio-driven talking head generation has drawn much attention in recent years, and many efforts have been made in lip-sync, expressive facial expressions, natural head pose generation, and high video quality. However, no model has yet led…

Computer Vision and Pattern Recognition · Computer Science 2023-12-08 Xusen Sun , Longhao Zhang , Hao Zhu , Peng Zhang , Bang Zhang , Xinya Ji , Kangneng Zhou , Daiheng Gao , Liefeng Bo , Xun Cao

Gaussian splatting enables fast novel view synthesis in static 3D environments. However, reconstructing real-world environments remains challenging as distractors or occluders break the multi-view consistency assumption required for…

Computer Vision and Pattern Recognition · Computer Science 2025-03-27 Yihao Wang , Marcus Klasson , Matias Turkulainen , Shuzhe Wang , Juho Kannala , Arno Solin

3D human generation is an important problem with a wide range of applications in computer vision and graphics. Despite recent progress in generative AI such as diffusion models or rendering methods like Neural Radiance Fields or Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2025-06-06 Maksym Ivashechkin , Oscar Mendez , Richard Bowden
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