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Cross-modal systems trained on 2D visual inputs are presented with a dimensional shift when processing 3D scenes. An in-scene camera bridges the dimensionality gap but requires learning a control module. We introduce a new method that…

Computer Vision and Pattern Recognition · Computer Science 2026-01-01 Jason Armitage , Rico Sennnrich

Filmmaking and animation production often require sophisticated techniques for coordinating camera transitions and object movements, typically involving labor-intensive real-world capturing. Despite advancements in generative AI for video…

Computer Vision and Pattern Recognition · Computer Science 2024-06-24 Yaowei Li , Xintao Wang , Zhaoyang Zhang , Zhouxia Wang , Ziyang Yuan , Liangbin Xie , Yuexian Zou , Ying Shan

Text-to-video generation has been dominated by diffusion-based or autoregressive models. These novel models provide plausible versatility, but are criticized for improper physical motion, shading and illumination, camera motion, and…

Computer Vision and Pattern Recognition · Computer Science 2025-05-06 Liu He , Yizhi Song , Hejun Huang , Pinxin Liu , Yunlong Tang , Daniel Aliaga , Xin Zhou

Autonomous camera systems are often subjected to an optimization/filtering operation to smoothen and stabilize the rough trajectory estimates. Most common filtering techniques do reduce the irregularities in data; however, they fail to…

Computer Vision and Pattern Recognition · Computer Science 2020-05-28 Sudheer Achary , K L Bhanu Moorthy , Syed Ashar Javed , Nikita Shravan , Vineet Gandhi , Anoop Namboodiri

We propose a method for generating video-realistic animations of real humans under user control. In contrast to conventional human character rendering, we do not require the availability of a production-quality photo-realistic 3D model of…

Computer Vision and Pattern Recognition · Computer Science 2019-05-13 Lingjie Liu , Weipeng Xu , Michael Zollhoefer , Hyeongwoo Kim , Florian Bernard , Marc Habermann , Wenping Wang , Christian Theobalt

This paper presents a method that allows users to design cinematic video shots in the context of image-to-video generation. Shot design, a critical aspect of filmmaking, involves meticulously planning both camera movements and object…

Computer Vision and Pattern Recognition · Computer Science 2025-02-07 Jinbo Xing , Long Mai , Cusuh Ham , Jiahui Huang , Aniruddha Mahapatra , Chi-Wing Fu , Tien-Tsin Wong , Feng Liu

Controllable and physically grounded egocentric video generation is essential for embodied agents to reason about how their own and others' actions manifest and change the world. Compared to generic video synthesis, egocentric generation is…

Computer Vision and Pattern Recognition · Computer Science 2026-05-27 Qiao Gu , Lingni Ma , Adam W Harley , Richard Newcombe , Florian Shkurti , Julian Straub

The automatic movie dubbing model generates vivid speech from given scripts, replicating a speaker's timbre from a brief timbre prompt while ensuring lip-sync with the silent video. Existing approaches simulate a simplified workflow where…

Computation and Language · Computer Science 2025-11-19 Rui Liu , Yuan Zhao , Zhenqi Jia

Humans excel at forecasting the future dynamics of a scene given just a single image. Video generation models that can mimic this ability are an essential component for intelligent systems. Recent approaches have improved temporal coherence…

Computer Vision and Pattern Recognition · Computer Science 2026-05-18 Melonie de Almeida , Daniela Ivanova , Tong Shi , John H. Williamson , Paul Henderson

Simulation is crucial for developing and evaluating autonomous vehicle (AV) systems. Recent literature builds on a new generation of generative models to synthesize highly realistic images for full-stack simulation. However, purely…

Computer Vision and Pattern Recognition · Computer Science 2025-06-25 Zehao Zhu , Yuliang Zou , Chiyu Max Jiang , Bo Sun , Vincent Casser , Xiukun Huang , Jiahao Wang , Zhenpei Yang , Ruiqi Gao , Leonidas Guibas , Mingxing Tan , Dragomir Anguelov

Recent video generation models have achieved remarkable progress and are now deployed in film, social media production, and advertising. Beyond their creative potential, such models also hold promise as world simulators for robotics and…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 David Romero , Ariana Bermudez , Viacheslav Iablochnikov , Hao Li , Fabio Pizzati , Ivan Laptev

Recent advancements in video generation have been greatly driven by video diffusion models, with camera motion control emerging as a crucial challenge in creating view-customized visual content. This paper introduces trajectory attention, a…

Computer Vision and Pattern Recognition · Computer Science 2024-12-02 Zeqi Xiao , Wenqi Ouyang , Yifan Zhou , Shuai Yang , Lei Yang , Jianlou Si , Xingang Pan

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

Existing generative approaches for guided image synthesis of multi-object scenes typically rely on 2D controls in the image or text space. As a result, these methods struggle to maintain and respect consistent three-dimensional geometric…

Computer Vision and Pattern Recognition · Computer Science 2025-08-05 Léopold Maillard , Tom Durand , Adrien Ramanana Rahary , Maks Ovsjanikov

We present CineMPC, an algorithm to autonomously control a UAV-borne video camera in a nonlinear Model Predicted Control (MPC) loop. CineMPC controls both the position and orientation of the camera -- the camera extrinsics -- as well as the…

Robotics · Computer Science 2022-02-23 Pablo Pueyo , Eduardo Montijano , Ana C. Murillo , Mac Schwager

Digital humans and, especially, 3D facial avatars have raised a lot of attention in the past years, as they are the backbone of several applications like immersive telepresence in AR or VR. Despite the progress, facial avatars reconstructed…

Computer Vision and Pattern Recognition · Computer Science 2023-11-27 Berna Kabadayi , Wojciech Zielonka , Bharat Lal Bhatnagar , Gerard Pons-Moll , Justus Thies

Creating large-scale interactive 3D environments is essential for the development of Robotics and Embodied AI research. Current methods, including manual design, procedural generation, diffusion-based scene generation, and large language…

Computer Vision and Pattern Recognition · Computer Science 2024-11-18 Yian Wang , Xiaowen Qiu , Jiageng Liu , Zhehuan Chen , Jiting Cai , Yufei Wang , Tsun-Hsuan Wang , Zhou Xian , Chuang Gan

3D-controllable portrait synthesis has significantly advanced, thanks to breakthroughs in generative adversarial networks (GANs). However, it is still challenging to manipulate existing face images with precise 3D control. While…

Computer Vision and Pattern Recognition · Computer Science 2022-08-25 Yuchen Liu , Zhixin Shu , Yijun Li , Zhe Lin , Richard Zhang , S. Y. Kung

In this paper, we introduce a novel deep learning method for photo-realistic manipulation of the emotional state of actors in "in-the-wild" videos. The proposed method is based on a parametric 3D face representation of the actor in the…

Computer Vision and Pattern Recognition · Computer Science 2022-03-31 Foivos Paraperas Papantoniou , Panagiotis P. Filntisis , Petros Maragos , Anastasios Roussos

Synthesizing camera movements from music and dance is highly challenging due to the contradicting requirements and complexities of dance cinematography. Unlike human movements, which are always continuous, dance camera movements involve…

Computer Vision and Pattern Recognition · Computer Science 2024-09-24 Zixuan Wang , Jiayi Li , Xiaoyu Qin , Shikun Sun , Songtao Zhou , Jia Jia , Jiebo Luo
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