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There has been extensive progress in the reconstruction and generation of 4D scenes from monocular casually-captured video. While these tasks rely heavily on known camera poses, the problem of finding such poses using structure-from-motion…

Computer Vision and Pattern Recognition · Computer Science 2024-12-02 Lily Goli , Sara Sabour , Mark Matthews , Marcus Brubaker , Dmitry Lagun , Alec Jacobson , David J. Fleet , Saurabh Saxena , Andrea Tagliasacchi

Video frame interpolation typically involves two steps: motion estimation and pixel synthesis. Such a two-step approach heavily depends on the quality of motion estimation. This paper presents a robust video frame interpolation method that…

Computer Vision and Pattern Recognition · Computer Science 2017-03-23 Simon Niklaus , Long Mai , Feng Liu

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

We propose a novel inference technique based on a pretrained diffusion model for text-conditional video generation. Our approach, called FIFO-Diffusion, is conceptually capable of generating infinitely long videos without additional…

Computer Vision and Pattern Recognition · Computer Science 2024-11-05 Jihwan Kim , Junoh Kang , Jinyoung Choi , Bohyung Han

The body movements accompanying speech aid speakers in expressing their ideas. Co-speech motion generation is one of the important approaches for synthesizing realistic avatars. Due to the intricate correspondence between speech and motion,…

Multimedia · Computer Science 2024-08-28 Sen Wang , Jiangning Zhang , Xin Tan , Zhifeng Xie , Chengjie Wang , Lizhuang Ma

Objects moving at high speed appear significantly blurred when captured with cameras. The blurry appearance is especially ambiguous when the object has complex shape or texture. In such cases, classical methods, or even humans, are unable…

Computer Vision and Pattern Recognition · Computer Science 2021-11-23 Denys Rozumnyi , Martin R. Oswald , Vittorio Ferrari , Jiri Matas , Marc Pollefeys

The technology for Visual Odometry (VO) that estimates the position and orientation of the moving object through analyzing the image sequences captured by on-board cameras, has been well investigated with the rising interest in autonomous…

Computer Vision and Pattern Recognition · Computer Science 2021-05-21 Ran Zhu , Mingkun Yang , Wang Liu , Rujun Song , Bo Yan , Zhuoling Xiao

Diffusion models have been widely used for conditional data cross-modal generation tasks such as text-to-image and text-to-video. However, state-of-the-art models still fail to align the generated visual concepts with high-level semantics…

Computer Vision and Pattern Recognition · Computer Science 2024-03-26 Zizhao Hu , Shaochong Jia , Mohammad Rostami

Deep learning models have emerged as a powerful tool for various medical applications. However, their success depends on large, high-quality datasets that are challenging to obtain due to privacy concerns and costly annotation. Generative…

Computer Vision and Pattern Recognition · Computer Science 2025-03-04 Milad Yazdani , Yasamin Medghalchi , Pooria Ashrafian , Ilker Hacihaliloglu , Dena Shahriari

Recent work in Video Frame Interpolation (VFI) tries to formulate VFI as a diffusion-based conditional image generation problem, synthesizing the intermediate frame given a random noise and neighboring frames. Due to the relatively high…

Computer Vision and Pattern Recognition · Computer Science 2024-11-28 Zonglin Lyu , Ming Li , Jianbo Jiao , Chen Chen

The remarkable generative capabilities of diffusion models have motivated extensive research in both image and video editing. Compared to video editing which faces additional challenges in the time dimension, image editing has witnessed the…

Computer Vision and Pattern Recognition · Computer Science 2024-05-28 Wenqi Ouyang , Yi Dong , Lei Yang , Jianlou Si , Xingang Pan

We present AnaMoDiff, a novel diffusion-based method for 2D motion analogies that is applied to raw, unannotated videos of articulated characters. Our goal is to accurately transfer motions from a 2D driving video onto a source character,…

Computer Vision and Pattern Recognition · Computer Science 2024-02-07 Maham Tanveer , Yizhi Wang , Ruiqi Wang , Nanxuan Zhao , Ali Mahdavi-Amiri , Hao Zhang

Hand-Object Interaction (HOI) generation has significant application potential. However, current 3D HOI motion generation approaches heavily rely on predefined 3D object models and lab-captured motion data, limiting generalization…

Computer Vision and Pattern Recognition · Computer Science 2025-06-06 Lingwei Dang , Ruizhi Shao , Hongwen Zhang , Wei Min , Yebin Liu , Qingyao Wu

Portrait animation aims to generate photo-realistic videos from a single source image by reenacting the expression and pose from a driving video. While early methods relied on 3D morphable models or feature warping techniques, they often…

Computer Vision and Pattern Recognition · Computer Science 2025-09-23 Mallikarjun B. R. , Fei Yin , Vikram Voleti , Nikita Drobyshev , Maksim Lapin , Aaryaman Vasishta , Varun Jampani

While recent text-to-video models excel at generating diverse scenes, they struggle with precise motion control, particularly for complex, multi-subject motions. Although methods for single-motion customization have been developed to…

Computer Vision and Pattern Recognition · Computer Science 2025-10-28 Youcan Xu , Zhen Wang , Jiaxin Shi , Kexin Li , Feifei Shao , Jun Xiao , Yi Yang , Jun Yu , Long Chen

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

Safety-critical applications, such as autonomous driving, require extensive multimodal data for rigorous testing. Methods based on synthetic data are gaining prominence due to the cost and complexity of gathering real-world data but require…

Computer Vision and Pattern Recognition · Computer Science 2025-04-23 Alexandru Buburuzan , Anuj Sharma , John Redford , Puneet K. Dokania , Romain Mueller

Generating realistic and physically plausible 3D Human-Object Interactions (HOI) remains a key challenge in motion generation. One primary reason is that describing these physical constraints with words alone is difficult. To address this…

Computer Vision and Pattern Recognition · Computer Science 2026-03-26 Songjin Cai , Linjie Zhong , Ling Guo , Changxing Ding

Seamlessly moving objects within a scene is a common requirement for image editing, but it is still a challenge for existing editing methods. Especially for real-world images, the occlusion situation further increases the difficulty. The…

Computer Vision and Pattern Recognition · Computer Science 2025-04-03 Zheng-Peng Duan , Jiawei Zhang , Siyu Liu , Zheng Lin , Chun-Le Guo , Dongqing Zou , Jimmy Ren , Chongyi Li

Since videos record objects moving coherently, adjacent video frames have commonness (similar object appearances) and uniqueness (slightly changed postures). To prevent redundant modeling of common video signals, we propose a novel…

Computer Vision and Pattern Recognition · Computer Science 2024-10-03 Mingzhen Sun , Weining Wang , Xinxin Zhu , Jing Liu