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Related papers: Choreographing a World of Dynamic Objects

200 papers

Cinematic storytelling is profoundly shaped by the artful manipulation of photographic elements such as depth of field and exposure. These effects are crucial in conveying mood and creating aesthetic appeal. However, controlling these…

Computer Vision and Pattern Recognition · Computer Science 2025-11-18 Huiqiang Sun , Liao Shen , Zhan Peng , Kun Wang , Size Wu , Yuhang Zang , Tianqi Liu , Zihao Huang , Xingyu Zeng , Zhiguo Cao , Wei Li , Chen Change Loy

Scene generation has extensive industrial applications, demanding both high realism and precise control over geometry and appearance. Language-driven retrieval methods compose plausible scenes from a large object database, but overlook…

Computer Vision and Pattern Recognition · Computer Science 2026-03-23 Zhifei Yang , Guangyao Zhai , Keyang Lu , YuYang Yin , Chao Zhang , Zhen Xiao , Jieyi Long , Nassir Navab , Yikai Wang

Many high-level video understanding methods require input in the form of object proposals. Currently, such proposals are predominantly generated with the help of networks that were trained for detecting and segmenting a set of known object…

Computer Vision and Pattern Recognition · Computer Science 2020-05-22 Aljosa Osep , Paul Voigtlaender , Mark Weber , Jonathon Luiten , Bastian Leibe

We introduce a method to synthesize animator guided human motion across 3D scenes. Given a set of sparse (3 or 4) joint locations (such as the location of a person's hand and two feet) and a seed motion sequence in a 3D scene, our method…

Computer Vision and Pattern Recognition · Computer Science 2025-02-04 Aymen Mir , Xavier Puig , Angjoo Kanazawa , Gerard Pons-Moll

We introduce the dynamic grasp synthesis task: given an object with a known 6D pose and a grasp reference, our goal is to generate motions that move the object to a target 6D pose. This is challenging, because it requires reasoning about…

Computer Vision and Pattern Recognition · Computer Science 2022-04-18 Sammy Christen , Muhammed Kocabas , Emre Aksan , Jemin Hwangbo , Jie Song , Otmar Hilliges

Scalability in terms of object density in a scene is a primary challenge in unsupervised sequential object-oriented representation learning. Most of the previous models have been shown to work only on scenes with a few objects. In this…

Machine Learning · Computer Science 2020-03-06 Jindong Jiang , Sepehr Janghorbani , Gerard de Melo , Sungjin Ahn

As pretrained text-to-image diffusion models become increasingly powerful, recent efforts have been made to distill knowledge from these text-to-image pretrained models for optimizing a text-guided 3D model. Most of the existing methods…

Computer Vision and Pattern Recognition · Computer Science 2024-06-12 Gege Gao , Weiyang Liu , Anpei Chen , Andreas Geiger , Bernhard Schölkopf

Existing techniques for dynamic scene reconstruction from multiple wide-baseline cameras primarily focus on reconstruction in controlled environments, with fixed calibrated cameras and strong prior constraints. This paper introduces a…

Computer Vision and Pattern Recognition · Computer Science 2020-08-04 Armin Mustafa , Marco Volino , Hansung Kim , Jean-Yves Guillemaut , Adrian Hilton

Recent developments in 2D visual generation have been remarkably successful. However, 3D and 4D generation remain challenging in real-world applications due to the lack of large-scale 4D data and effective model design. In this paper, we…

Computer Vision and Pattern Recognition · Computer Science 2024-11-06 Yuyang Zhao , Chung-Ching Lin , Kevin Lin , Zhiwen Yan , Linjie Li , Zhengyuan Yang , Jianfeng Wang , Gim Hee Lee , Lijuan Wang

Functional 3D scene graphs offer a versatile and flexible representation for 3D scene understanding and robotic manipulation, defined by object nodes, interactive elements, and functional relationship edges. However, their potential remains…

Video-based world models have recently garnered increasing attention for their ability to synthesize diverse and dynamic visual environments. In this paper, we focus on shared world modeling, where a model generates multiple videos from a…

Computer Vision and Pattern Recognition · Computer Science 2025-12-03 Fan Wu , Jiacheng Wei , Ruibo Li , Yi Xu , Junyou Li , Deheng Ye , Guosheng Lin

While remarkable success has been achieved through diffusion-based 3D generative models for shapes, 4D generative modeling remains challenging due to the complexity of object deformations over time. We propose DNF, a new 4D representation…

Computer Vision and Pattern Recognition · Computer Science 2024-12-09 Xinyi Zhang , Naiqi Li , Angela Dai

Cinematic video production requires control over scene-subject composition and camera movement, but live-action shooting remains costly due to the need for constructing physical sets. To address this, we introduce the task of cinematic…

Computer Vision and Pattern Recognition · Computer Science 2026-02-09 Kaiyi Huang , Yukun Huang , Yu Li , Jianhong Bai , Xintao Wang , Zinan Lin , Xuefei Ning , Jiwen Yu , Pengfei Wan , Yu Wang , Xihui Liu

Designing complex 3D scenes has been a tedious, manual process requiring domain expertise. Emerging text-to-3D generative models show great promise for making this task more intuitive, but existing approaches are limited to object-level…

Computer Vision and Pattern Recognition · Computer Science 2023-03-24 Ryan Po , Gordon Wetzstein

Recent advancements in video generation models have significantly improved their ability to follow text prompts. However, the customization of dynamic visual effects, defined as temporally evolving and appearance-driven visual phenomena…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Rui Zhao , Mike Zheng Shou

This paper contains analysis of main modern approaches to dynamic code generation, in particular generation of new classes of objects during program execution. The main attention was paid to universal exploiters of homogeneous classes of…

Software Engineering · Computer Science 2018-11-20 Dmytro O. Terletskyi

Diffusion models have achieved impressive performance in video generation, but their iterative denoising process remains computationally expensive due to the large number of tokens processed at each timestep. Recently, progressive…

Computer Vision and Pattern Recognition · Computer Science 2026-05-21 Shikang Zheng , Jingkai Huang , Jiacheng Liu , Guantao Chen , Lixuan , Yuqi Lin , Peiliang Cai , Linfeng Zhang

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

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

The blooming of virtual reality and augmented reality (VR/AR) technologies has driven an increasing demand for the creation of high-quality, immersive, and dynamic environments. However, existing generative techniques either focus solely on…

Computer Vision and Pattern Recognition · Computer Science 2024-10-04 Renjie Li , Panwang Pan , Bangbang Yang , Dejia Xu , Shijie Zhou , Xuanyang Zhang , Zeming Li , Achuta Kadambi , Zhangyang Wang , Zhengzhong Tu , Zhiwen Fan
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