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We present a method for generating video sequences with coherent motion between a pair of input key frames. We adapt a pretrained large-scale image-to-video diffusion model (originally trained to generate videos moving forward in time from…

Computer Vision and Pattern Recognition · Computer Science 2025-02-13 Xiaojuan Wang , Boyang Zhou , Brian Curless , Ira Kemelmacher-Shlizerman , Aleksander Holynski , Steven M. Seitz

Recent advances in diffusion-based and controllable video generation have enabled high-quality and temporally coherent video synthesis, laying the groundwork for immersive interactive gaming experiences. However, current methods face…

Computer Vision and Pattern Recognition · Computer Science 2025-06-23 Jiaqi Li , Junshu Tang , Zhiyong Xu , Longhuang Wu , Yuan Zhou , Shuai Shao , Tianbao Yu , Zhiguo Cao , Qinglin Lu

We propose a novel task of text-controlled human object interaction generation in 3D scenes with movable objects. Existing human-scene interaction datasets suffer from insufficient interaction categories and typically only consider…

Computer Vision and Pattern Recognition · Computer Science 2025-09-30 Xinhao Cai , Minghang Zheng , Xin Jin , Yang Liu

Though action recognition in videos has achieved great success recently, it remains a challenging task due to the massive computational cost. Designing lightweight networks is a possible solution, but it may degrade the recognition…

Computer Vision and Pattern Recognition · Computer Science 2020-02-11 Wenhao Wu , Dongliang He , Xiao Tan , Shifeng Chen , Yi Yang , Shilei Wen

In this work, we present a data-driven framework for generating diverse in-betweening motions for kinematic characters. Our approach injects dynamic conditions and explicit motion controls into the procedure of motion transitions. Notably,…

Graphics · Computer Science 2024-10-02 Yuchen Chu , Zeshi Yang

We propose HyperDynamics, a dynamics meta-learning framework that conditions on an agent's interactions with the environment and optionally its visual observations, and generates the parameters of neural dynamics models based on inferred…

Robotics · Computer Science 2021-03-18 Zhou Xian , Shamit Lal , Hsiao-Yu Tung , Emmanouil Antonios Platanios , Katerina Fragkiadaki

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

Instructional video generation is an emerging task that aims to synthesize coherent demonstrations of procedural activities from textual descriptions. Such capability has broad implications for content creation, education, and human-AI…

Computer Vision and Pattern Recognition · Computer Science 2025-12-16 Cheeun Hong , German Barquero , Fadime Sener , Markos Georgopoulos , Edgar Schönfeld , Stefan Popov , Yuming Du , Oscar Mañas , Albert Pumarola

Video inpainting is the task of filling a region in a video in a visually convincing manner. It is very challenging due to the high dimensionality of the data and the temporal consistency required for obtaining convincing results. Recently,…

Computer Vision and Pattern Recognition · Computer Science 2025-04-29 Nicolas Cherel , Andrés Almansa , Yann Gousseau , Alasdair Newson

Recent video diffusion models have demonstrated their great capability in generating visually-pleasing results, while synthesizing the correct physical effects in generated videos remains challenging. The complexity of real-world motions,…

Computer Vision and Pattern Recognition · Computer Science 2025-10-08 Ke Zhang , Cihan Xiao , Jiacong Xu , Yiqun Mei , Vishal M. Patel

Generating visual instructions in a given context is essential for developing interactive world simulators. While prior works address this problem through either text-guided image manipulation or video prediction, these tasks are typically…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Yujiang Pu , Zhanbo Huang , Vishnu Boddeti , Yu Kong

In this work, we introduce a novel approach for creating controllable dynamics in 3D-generated Gaussians using casually captured reference videos. Our method transfers the motion of objects from reference videos to a variety of generated 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-07-09 Zhoujie Fu , Jiacheng Wei , Wenhao Shen , Chaoyue Song , Xiaofeng Yang , Fayao Liu , Xulei Yang , Guosheng Lin

Pretrained video generation models provide strong priors for robot control, but existing unified world action models still struggle to decode reliable actions without substantial robot-specific training. We attribute this limitation to a…

Robotics · Computer Science 2026-04-14 Liaoyuan Fan , Zetian Xu , Chen Cao , Wenyao Zhang , Mingqi Yuan , Jiayu Chen

Generative models often treat continuous data and discrete events as separate processes, creating a gap in modeling complex systems where they interact synchronously. To bridge this gap, we introduce JointDiff, a novel diffusion framework…

Machine Learning · Computer Science 2026-01-30 Guillem Capellera , Luis Ferraz , Antonio Rubio , Alexandre Alahi , Antonio Agudo

Recent generative video world models aim to simulate visual environment evolution, allowing an observer to interactively explore the scene via camera control. However, they implicitly assume that the world only evolves within the observer's…

Computer Vision and Pattern Recognition · Computer Science 2026-03-25 Zicheng Duan , Jiatong Xia , Zeyu Zhang , Wenbo Zhang , Gengze Zhou , Chenhui Gou , Yefei He , Feng Chen , Xinyu Zhang , Lingqiao Liu

World models play a crucial role in understanding and predicting the dynamics of the world, which is essential for video generation. However, existing world models are confined to specific scenarios such as gaming or driving, limiting their…

Computer Vision and Pattern Recognition · Computer Science 2024-01-19 Xiaofeng Wang , Zheng Zhu , Guan Huang , Boyuan Wang , Xinze Chen , Jiwen Lu

Modeling sounds emitted from physical object interactions is critical for immersive perceptual experiences in real and virtual worlds. Traditional methods of impact sound synthesis use physics simulation to obtain a set of physics…

Computer Vision and Pattern Recognition · Computer Science 2023-07-11 Kun Su , Kaizhi Qian , Eli Shlizerman , Antonio Torralba , Chuang Gan

Generating high-quality whole-body human object interaction motion sequences is becoming increasingly important in various fields such as animation, VR/AR, and robotics. The main challenge of this task lies in determining the level of…

Computer Vision and Pattern Recognition · Computer Science 2024-12-31 Yonghao Zhang , Qiang He , Yanguang Wan , Yinda Zhang , Xiaoming Deng , Cuixia Ma , Hongan Wang

Text-conditioned motion synthesis has made remarkable progress with the emergence of diffusion models. However, the majority of these motion diffusion models are primarily designed for a single character and overlook multi-human…

Computer Vision and Pattern Recognition · Computer Science 2024-11-22 Zhenzhi Wang , Jingbo Wang , Yixuan Li , Dahua Lin , Bo Dai

Traditional control and planning for robotic manipulation heavily rely on precise physical models and predefined action sequences. While effective in structured environments, such approaches often fail in real-world scenarios due to…

Robotics · Computer Science 2025-08-08 Jin Wang , Weijie Wang , Boyuan Deng , Heng Zhang , Rui Dai , Nikos Tsagarakis