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We introduce bounded generation as a generalized task to control video generation to synthesize arbitrary camera and subject motion based only on a given start and end frame. Our objective is to fully leverage the inherent generalization…

Computer Vision and Pattern Recognition · Computer Science 2024-03-22 Haiwen Feng , Zheng Ding , Zhihao Xia , Simon Niklaus , Victoria Abrevaya , Michael J. Black , Xuaner Zhang

Video frame interpolation is the task of creating an interframe between two adjacent frames along the time axis. So, instead of simply averaging two adjacent frames to create an intermediate image, this operation should maintain semantic…

Computer Vision and Pattern Recognition · Computer Science 2021-06-30 Saem Park , Donghoon Han , Nojun Kwak

Recent advancements in generative models have ignited substantial interest in dynamic 3D content creation (\ie, 4D generation). Existing approaches primarily rely on Score Distillation Sampling (SDS) to infer novel-view videos, typically…

Computer Vision and Pattern Recognition · Computer Science 2025-01-06 Hanxin Zhu , Tianyu He , Xiqian Yu , Junliang Guo , Zhibo Chen , Jiang Bian

We introduce Drag4D, an interactive framework that integrates object motion control within text-driven 3D scene generation. This framework enables users to define 3D trajectories for the 3D objects generated from a single image, seamlessly…

Computer Vision and Pattern Recognition · Computer Science 2025-09-29 Minjun Kang , Inkyu Shin , Taeyeop Lee , In So Kweon , Kuk-Jin Yoon

Understanding and predicting dynamics of the physical world can enhance a robot's ability to plan and interact effectively in complex environments. While recent video generation models have shown strong potential in modeling dynamic scenes,…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Zeyi Liu , Shuang Li , Eric Cousineau , Siyuan Feng , Benjamin Burchfiel , Shuran Song

Video frame interpolation aims to synthesize realistic intermediate frames between given endpoints while adhering to specific motion semantics. While recent generative models have improved visual fidelity, they predominantly operate in a…

Computer Vision and Pattern Recognition · Computer Science 2026-04-03 Lingyu Liu , Yaxiong Wang , Li Zhu , Zhedong Zheng

Upsampling videos of human activity is an interesting yet challenging task with many potential applications ranging from gaming to entertainment and sports broadcasting. The main difficulty in synthesizing video frames in this setting stems…

Computer Vision and Pattern Recognition · Computer Science 2021-11-02 Hsuan-I Ho , Xu Chen , Jie Song , Otmar Hilliges

Generating realistic human videos remains a challenging task, with the most effective methods currently relying on a human motion sequence as a control signal. Existing approaches often use existing motion extracted from other videos, which…

Computer Vision and Pattern Recognition · Computer Science 2024-12-18 Hsin-Ping Huang , Yang Zhou , Jui-Hsien Wang , Difan Liu , Feng Liu , Ming-Hsuan Yang , Zhan Xu

Recent advancements in 2D/3D generative techniques have facilitated the generation of dynamic 3D objects from monocular videos. Previous methods mainly rely on the implicit neural radiance fields (NeRF) or explicit Gaussian Splatting as the…

Computer Vision and Pattern Recognition · Computer Science 2024-10-10 Zhiqi Li , Yiming Chen , Peidong Liu

Text-to-4D generation has recently been demonstrated viable by integrating a 2D image diffusion model with a video diffusion model. However, existing models tend to produce results with inconsistent motions and geometric structures over…

Graphics · Computer Science 2024-08-19 Ce Chen , Shaoli Huang , Xuelin Chen , Guangyi Chen , Xiaoguang Han , Kun Zhang , Mingming Gong

Standard video frame interpolation methods first estimate optical flow between input frames and then synthesize an intermediate frame guided by motion. Recent approaches merge these two steps into a single convolution process by convolving…

Computer Vision and Pattern Recognition · Computer Science 2017-08-08 Simon Niklaus , Long Mai , Feng Liu

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

Video interpolation is an important problem in computer vision, which helps overcome the temporal limitation of camera sensors. Existing video interpolation methods usually assume uniform motion between consecutive frames and use linear…

Computer Vision and Pattern Recognition · Computer Science 2019-11-05 Xiangyu Xu , Li Siyao , Wenxiu Sun , Qian Yin , Ming-Hsuan Yang

Video frame interpolation aims to synthesize one or multiple frames between two consecutive frames in a video. It has a wide range of applications including slow-motion video generation, frame-rate up-scaling and developing video codecs.…

Computer Vision and Pattern Recognition · Computer Science 2022-04-14 Saikat Dutta , Arulkumar Subramaniam , Anurag Mittal

Generating smooth animations from a limited number of sequential observations has a number of applications in vision. For example, it can be used to increase number of frames per second, or generating a new trajectory only based on first…

Computer Vision and Pattern Recognition · Computer Science 2022-05-11 Jurijs Nazarovs , Zhichun Huang

Video Frame Interpolation synthesizes non-existent images between adjacent frames, with the aim of providing a smooth and consistent visual experience. Two approaches for solving this challenging task are optical flow based and kernel-based…

Computer Vision and Pattern Recognition · Computer Science 2021-05-13 Xi Li , Meng Cao , Yingying Tang , Scott Johnston , Zhendong Hong , Huimin Ma , Jiulong Shan

With the success of 2D and 3D visual generative models, there is growing interest in generating 4D content. Existing methods primarily rely on text prompts to produce 4D content, but they often fall short of accurately defining complex or…

Computer Vision and Pattern Recognition · Computer Science 2025-06-26 Hao Zhang , Di Chang , Fang Li , Mohammad Soleymani , Narendra Ahuja

Generating non-existing frames from a consecutive video sequence has been an interesting and challenging problem in the video processing field. Typical kernel-based interpolation methods predict pixels with a single convolution process that…

Computer Vision and Pattern Recognition · Computer Science 2021-03-05 Xianhang Cheng , Zhenzhong Chen

The advancement of 4D (i.e., sequential 3D) generation opens up new possibilities for lifelike experiences in various applications, where users can explore dynamic objects or characters from any viewpoint. Meanwhile, video generative models…

Graphics · Computer Science 2025-04-08 Yikai Wang , Guangce Liu , Xinzhou Wang , Zilong Chen , Jiafang Li , Xin Liang , Fuchun Sun , Jun Zhu

World-model-based imagine-then-act becomes a promising paradigm for robotic manipulation, yet existing approaches typically support either purely image-based forecasting or reasoning over partial 3D geometry, limiting their ability to…

Computer Vision and Pattern Recognition · Computer Science 2026-05-27 Jiaxu Wang , Yicheng Jiang , Tianlun He , Jingkai Sun , Qiang Zhang , Junhao He , Jiahang Cao , Zesen Gan , Mingyuan Sun , Qiming Shao , Xiangyu Yue