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Related papers: 3D-Aware Implicit Motion Control for View-Adaptive…

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Despite remarkable progress in video generation, maintaining long-term scene consistency upon revisiting previously explored areas remains challenging. Existing solutions rely either on explicitly constructing 3D geometry, which suffers…

Computer Vision and Pattern Recognition · Computer Science 2026-03-25 Jia Li , Han Yan , Yihang Chen , Siqi Li , Xibin Song , Yifu Wang , Jianfei Cai , Tien-Tsin Wong , Pan Ji

Motion-controllable image animation is a fundamental task with a wide range of potential applications. Recent works have made progress in controlling camera or object motion via various motion representations, while they still struggle to…

Computer Vision and Pattern Recognition · Computer Science 2025-03-11 Yingjie Chen , Yifang Men , Yuan Yao , Miaomiao Cui , Liefeng Bo

We extend multimodal transformers to include 3D camera motion as a conditioning signal for the task of video generation. Generative video models are becoming increasingly powerful, thus focusing research efforts on methods of controlling…

Computer Vision and Pattern Recognition · Computer Science 2024-05-24 Andrew Marmon , Grant Schindler , José Lezama , Dan Kondratyuk , Bryan Seybold , Irfan Essa

Video data is more cost-effective than motion capture data for learning 3D character motion controllers, yet synthesizing realistic and diverse behaviors directly from videos remains challenging. Previous approaches typically rely on…

Graphics · Computer Science 2025-12-10 Jianan Li , Xiao Chen , Tao Huang , Tien-Tsin Wong

While Multimodal Large Language Models demonstrate impressive semantic capabilities, they often suffer from spatial blindness, struggling with fine-grained geometric reasoning and physical dynamics. Existing solutions typically rely on…

Computer Vision and Pattern Recognition · Computer Science 2026-03-20 Xianjin Wu , Dingkang Liang , Tianrui Feng , Kui Xia , Yumeng Zhang , Xiaofan Li , Xiao Tan , Xiang Bai

Motion-controllable video generation is crucial for egocentric applications in virtual reality and embodied AI. However, existing methods often struggle to achieve 3D-consistent fine-grained hand articulation. By adopting on 2D trajectories…

Computer Vision and Pattern Recognition · Computer Science 2026-04-13 Chenyangguang Zhang , Botao Ye , Boqi Chen , Alexandros Delitzas , Fangjinhua Wang , Marc Pollefeys , Xi Wang

Significant progress has been made in text-to-video generation through the use of powerful generative models and large-scale internet data. However, substantial challenges remain in precisely controlling individual concepts within the…

Computer Vision and Pattern Recognition · Computer Science 2024-09-30 Hanxin Zhu , Tianyu He , Anni Tang , Junliang Guo , Zhibo Chen , Jiang Bian

Camera control has been extensively studied in conditioned video generation; however, performing precisely altering the camera trajectories while faithfully preserving the video content remains a challenging task. The mainstream approach to…

Computer Vision and Pattern Recognition · Computer Science 2026-02-02 Dong-Yu Chen , Yixin Guo , Shuojin Yang , Tai-Jiang Mu , Shi-Min Hu

Human motion generation is a significant pursuit in generative computer vision with widespread applications in film-making, video games, AR/VR, and human-robot interaction. Current methods mainly utilize either diffusion-based generative…

Computer Vision and Pattern Recognition · Computer Science 2025-02-03 Canxuan Gang

Recent advances in video diffusion models have enabled the generation of high-quality videos. However, these videos still suffer from unrealistic deformations, semantic violations, and physical inconsistencies that are largely rooted in the…

Computer Vision and Pattern Recognition · Computer Science 2025-11-04 Shurui Gui , Deep Anil Patel , Xiner Li , Martin Renqiang Min

Hand-Object Interaction (HOI) generation has significant application potential. However, current 3D HOI motion generation approaches heavily rely on predefined 3D object models and lab-captured motion data, limiting generalization…

Computer Vision and Pattern Recognition · Computer Science 2025-06-06 Lingwei Dang , Ruizhi Shao , Hongwen Zhang , Wei Min , Yebin Liu , Qingyao Wu

We introduce a novel approach for high-resolution talking head generation from a single image and audio input. Prior methods using explicit face models, like 3D morphable models (3DMM) and facial landmarks, often fall short in generating…

Computer Vision and Pattern Recognition · Computer Science 2024-12-11 Sejong Yang , Seoung Wug Oh , Yang Zhou , Seon Joo Kim

A natural approach to generative modeling of videos is to represent them as a composition of moving objects. Recent works model a set of 2D sprites over a slowly-varying background, but without considering the underlying 3D scene that gives…

Computer Vision and Pattern Recognition · Computer Science 2021-03-26 Paul Henderson , Christoph H. Lampert

Generative video modeling has emerged as a compelling tool to zero-shot reason about plausible physical interactions for open-world manipulation. Yet, it remains a challenge to translate such human-led motions into the low-level actions…

Robotics · Computer Science 2026-01-01 Karthik Dharmarajan , Wenlong Huang , Jiajun Wu , Li Fei-Fei , Ruohan Zhang

Text-driven 3D editing enables user-friendly 3D object or scene editing with text instructions. Due to the lack of multi-view consistency priors, existing methods typically resort to employing 2D generation or editing models to process each…

Computer Vision and Pattern Recognition · Computer Science 2025-12-02 Liyi Chen , Ruihuang Li , Guowen Zhang , Pengfei Wang , Lei Zhang

Generating human videos with realistic and controllable motions is a challenging task. While existing methods can generate visually compelling videos, they lack separate control over four key video elements: foreground subject, background…

Computer Vision and Pattern Recognition · Computer Science 2025-08-13 Jingyun Liang , Jingkai Zhou , Shikai Li , Chenjie Cao , Lei Sun , Yichen Qian , Weihua Chen , Fan Wang

Traditional 3D content creation tools empower users to bring their imagination to life by giving them direct control over a scene's geometry, appearance, motion, and camera path. Creating computer-generated videos, however, is a tedious…

Computer Vision and Pattern Recognition · Computer Science 2023-12-05 Shengqu Cai , Duygu Ceylan , Matheus Gadelha , Chun-Hao Paul Huang , Tuanfeng Yang Wang , Gordon Wetzstein

In this paper, we find that the generation of 3D human motions and 2D human videos is intrinsically coupled. 3D motions provide the structural prior for plausibility and consistency in videos, while pre-trained video models offer strong…

Computer Vision and Pattern Recognition · Computer Science 2026-04-13 Chengfeng Zhao , Jiazhi Shu , Yubo Zhao , Tianyu Huang , Jiahao Lu , Zekai Gu , Chengwei Ren , Zhiyang Dou , Qing Shuai , Yuan Liu

3D animation is central to modern visual media, yet traditional production pipelines remain labor-intensive, expertise-demanding, and computationally expensive. Recent AIGC-based approaches partially automate asset creation and rigging, but…

Computer Vision and Pattern Recognition · Computer Science 2025-12-22 Yupeng Zhu , Xiongzhen Zhang , Ye Chen , Bingbing Ni

Numerous works have recently integrated 3D camera control into foundational text-to-video models, but the resulting camera control is often imprecise, and video generation quality suffers. In this work, we analyze camera motion from a first…

Computer Vision and Pattern Recognition · Computer Science 2025-05-07 Sherwin Bahmani , Ivan Skorokhodov , Guocheng Qian , Aliaksandr Siarohin , Willi Menapace , Andrea Tagliasacchi , David B. Lindell , Sergey Tulyakov
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