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Humans naturally build mental models of object interactions and dynamics, allowing them to imagine how their surroundings will change if they take a certain action. While generative models today have shown impressive results on…

Computer Vision and Pattern Recognition · Computer Science 2024-08-15 Sruthi Sudhakar , Ruoshi Liu , Basile Van Hoorick , Carl Vondrick , Richard Zemel

We present WorldCanvas, a framework for promptable world events that enables rich, user-directed simulation by combining text, trajectories, and reference images. Unlike text-only approaches and existing trajectory-controlled image-to-video…

Computer Vision and Pattern Recognition · Computer Science 2025-12-19 Hanlin Wang , Hao Ouyang , Qiuyu Wang , Yue Yu , Yihao Meng , Wen Wang , Ka Leong Cheng , Shuailei Ma , Qingyan Bai , Yixuan Li , Cheng Chen , Yanhong Zeng , Xing Zhu , Yujun Shen , Qifeng Chen

We present a video generation model that accurately reproduces object motion, changes in camera viewpoint, and new content that arises over time. Existing video generation methods often fail to produce new content as a function of time…

Computer Vision and Pattern Recognition · Computer Science 2022-06-10 Tim Brooks , Janne Hellsten , Miika Aittala , Ting-Chun Wang , Timo Aila , Jaakko Lehtinen , Ming-Yu Liu , Alexei A. Efros , Tero Karras

We are given a video of a person performing a certain activity, from which we extract a controllable model. The model generates novel image sequences of that person, according to arbitrary user-defined control signals, typically marking the…

Machine Learning · Computer Science 2019-04-18 Oran Gafni , Lior Wolf , Yaniv Taigman

We present a portable multiscopic camera system with a dedicated model for novel view and time synthesis in dynamic scenes. Our goal is to render high-quality images for a dynamic scene from any viewpoint at any time using our portable…

Computer Vision and Pattern Recognition · Computer Science 2022-08-31 Tianjia Zhang , Yuen-Fui Lau , Qifeng Chen

Explorable 3D world generation from a single image or text prompt forms a cornerstone of spatial intelligence. Recent works utilize video model to achieve wide-scope and generalizable 3D world generation. However, existing approaches often…

Computer Vision and Pattern Recognition · Computer Science 2025-08-12 Zhongqi Yang , Wenhang Ge , Yuqi Li , Jiaqi Chen , Haoyuan Li , Mengyin An , Fei Kang , Hua Xue , Baixin Xu , Yuyang Yin , Eric Li , Yang Liu , Yikai Wang , Hao-Xiang Guo , Yahui Zhou

Pre-trained video models learn powerful priors for generating high-quality, temporally coherent content. While these models excel at temporal coherence, their dynamics are often constrained by the continuous nature of their training data.…

Computer Vision and Pattern Recognition · Computer Science 2025-12-02 Zhoujie Fu , Xianfang Zeng , Jinghong Lan , Xinyao Liao , Cheng Chen , Junyi Chen , Jiacheng Wei , Wei Cheng , Shiyu Liu , Yunuo Chen , Gang Yu , Guosheng Lin

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

World models have emerged as a powerful paradigm for building interactive simulation environments, with recent video-based approaches demonstrating impressive progress in generating visually plausible dynamics. However, because these models…

Artificial Intelligence · Computer Science 2026-05-15 Hongyu Wang , Jingquan Wang , Bocheng Zou , Radu Serban , Dan Negrut

GANs are able to perform generation and manipulation tasks, trained on a single video. However, these single video GANs require unreasonable amount of time to train on a single video, rendering them almost impractical. In this paper we…

Computer Vision and Pattern Recognition · Computer Science 2021-12-07 Niv Haim , Ben Feinstein , Niv Granot , Assaf Shocher , Shai Bagon , Tali Dekel , Michal Irani

3D content creation has long been a complex and time-consuming process, often requiring specialized skills and resources. While recent advancements have allowed for text-guided 3D object and scene generation, they still fall short of…

Computer Vision and Pattern Recognition · Computer Science 2024-08-06 Xingyi Li , Yizheng Wu , Jun Cen , Juewen Peng , Kewei Wang , Ke Xian , Zhe Wang , Zhiguo Cao , Guosheng Lin

Generating 3D worlds from text is a highly anticipated goal in computer vision. Existing works are limited by the degree of exploration they allow inside of a scene, i.e., produce streched-out and noisy artifacts when moving beyond central…

Computer Vision and Pattern Recognition · Computer Science 2025-09-17 Manuel-Andreas Schneider , Lukas Höllein , Matthias Nießner

Interactive world models continually generate video by responding to a user's actions, enabling open-ended generation capabilities. However, existing models typically lack a 3D representation of the environment, meaning 3D consistency must…

Computer Vision and Pattern Recognition · Computer Science 2026-03-05 Samuel Garcin , Thomas Walker , Steven McDonagh , Tim Pearce , Hakan Bilen , Tianyu He , Kaixin Wang , Jiang Bian

Generative models have emerged as an essential building block for many image synthesis and editing tasks. Recent advances in this field have also enabled high-quality 3D or video content to be generated that exhibits either multi-view or…

Computer Vision and Pattern Recognition · Computer Science 2023-08-10 Sherwin Bahmani , Jeong Joon Park , Despoina Paschalidou , Hao Tang , Gordon Wetzstein , Leonidas Guibas , Luc Van Gool , Radu Timofte

Aerial vehicles are revolutionizing the way film-makers can capture shots of actors by composing novel aerial and dynamic viewpoints. However, despite great advancements in autonomous flight technology, generating expressive camera…

Computer Vision and Pattern Recognition · Computer Science 2021-04-02 Rogerio Bonatti , Arthur Bucker , Sebastian Scherer , Mustafa Mukadam , Jessica Hodgins

We introduce a recipe for generating immersive 3D worlds from a single image by framing the task as an in-context learning problem for 2D inpainting models. This approach requires minimal training and uses existing generative models. Our…

Computer Vision and Pattern Recognition · Computer Science 2025-03-24 Katja Schwarz , Denys Rozumnyi , Samuel Rota Bulò , Lorenzo Porzi , Peter Kontschieder

Lightweight, controllable, and physically plausible human motion synthesis is crucial for animation, virtual reality, robotics, and human-computer interaction applications. Existing methods often compromise between computational efficiency,…

Computer Vision and Pattern Recognition · Computer Science 2025-01-29 Arvin Tashakori , Arash Tashakori , Gongbo Yang , Z. Jane Wang , Peyman Servati

Creating scenes for captured motions that achieve realistic human-scene interaction is crucial for 3D animation in movies or video games. As character motion is often captured in a blue-screened studio without real furniture or objects in…

Computer Vision and Pattern Recognition · Computer Science 2024-05-22 Jianan Li , Tao Huang , Qingxu Zhu , Tien-Tsin Wong

We propose an action-conditioned dynamics model that predicts scene changes caused by object and agent interactions in a viewpoint-invariant 3D neural scene representation space, inferred from RGB-D videos. In this 3D feature space, objects…

Robotics · Computer Science 2020-12-29 Hsiao-Yu Fish Tung , Zhou Xian , Mihir Prabhudesai , Shamit Lal , Katerina Fragkiadaki

Recent advances in Video Foundation Models (VFMs) have revolutionized human-centric video synthesis, yet fine-grained and independent editing of subjects and scenes remains a critical challenge. Recent attempts to incorporate richer…

Computer Vision and Pattern Recognition · Computer Science 2026-04-02 Fengyuan Yang , Luying Huang , Jiazhi Guan , Quanwei Yang , Dongwei Pan , Jianglin Fu , Haocheng Feng , Wei He , Kaisiyuan Wang , Hang Zhou , Angela Yao
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