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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 text-conditioned video diffusion have greatly improved video quality. However, these methods offer limited or sometimes no control to users on camera aspects, including dynamic camera motion, zoom, distorted lens and…

Computer Vision and Pattern Recognition · Computer Science 2024-12-31 Xi Wang , Robin Courant , Marc Christie , Vicky Kalogeiton

AI-generated content has attracted lots of attention recently, but photo-realistic video synthesis is still challenging. Although many attempts using GANs and autoregressive models have been made in this area, the visual quality and length…

Computer Vision and Pattern Recognition · Computer Science 2023-03-21 Yingqing He , Tianyu Yang , Yong Zhang , Ying Shan , Qifeng Chen

In this paper, we aim to improve the state-of-the-art video generative adversarial networks (GANs) with a view towards multi-functional applications. Our improved video GAN model does not separate foreground from background nor dynamic from…

Computer Vision and Pattern Recognition · Computer Science 2018-03-16 Bernhard Kratzwald , Zhiwu Huang , Danda Pani Paudel , Acharya Dinesh , Luc Van Gool

Talking face generation technology creates talking videos from arbitrary appearance and motion signal, with the "arbitrary" offering ease of use but also introducing challenges in practical applications. Existing methods work well with…

Computer Vision and Pattern Recognition · Computer Science 2024-03-27 Chao Liang , Jianwen Jiang , Tianyun Zhong , Gaojie Lin , Zhengkun Rong , Jiaqi Yang , Yongming Zhu

Foreground-aware image synthesis aims to generate images as well as their foreground masks. A common approach is to formulate an image as an masked blending of a foreground image and a background image. It is a challenging problem because…

Computer Vision and Pattern Recognition · Computer Science 2022-08-23 Jeongmin Bae , Mingi Kwon , Youngjung Uh

Pairwise pose estimation from images with little or no overlap is an open challenge in computer vision. Existing methods, even those trained on large-scale datasets, struggle in these scenarios due to the lack of identifiable…

Computer Vision and Pattern Recognition · Computer Science 2024-12-23 Ruojin Cai , Jason Y. Zhang , Philipp Henzler , Zhengqi Li , Noah Snavely , Ricardo Martin-Brualla

We introduce \textit{WonderVerse}, a simple but effective framework for generating extendable 3D scenes. Unlike existing methods that rely on iterative depth estimation and image inpainting, often leading to geometric distortions and…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Hao Feng , Zhi Zuo , Jia-Hui Pan , Ka-Hei Hui , Qi Dou , Jingyu Hu , Zhengzhe Liu

True video understanding requires making sense of non-lambertian scenes where the color of light arriving at the camera sensor encodes information about not just the last object it collided with, but about multiple mediums -- colored…

Computer Vision and Pattern Recognition · Computer Science 2019-04-05 Jean-Baptiste Alayrac , João Carreira , Andrew Zisserman

Generative image composition aims to regenerate the given foreground object in the background image to produce a realistic composite image. The existing methods are struggling to preserve the foreground details and adjust the foreground…

Computer Vision and Pattern Recognition · Computer Science 2025-04-07 Jiaxuan Chen , Bo Zhang , Qingdong He , Jinlong Peng , Li Niu

There has been exciting progress in generating images from natural language or layout conditions. However, these methods struggle to faithfully reproduce complex scenes due to the insufficient modeling of multiple objects and their…

Computer Vision and Pattern Recognition · Computer Science 2024-10-02 Yunnan Wang , Ziqiang Li , Zequn Zhang , Wenyao Zhang , Baao Xie , Xihui Liu , Wenjun Zeng , Xin Jin

Synthesis of diverse driving scenes serves as a crucial data augmentation technique for validating the robustness and generalizability of autonomous driving systems. Current methods aggregate high-definition (HD) maps and 3D bounding boxes…

Computer Vision and Pattern Recognition · Computer Science 2026-02-27 Zhechao Wang , Yiming Zeng , Lufan Ma , Zeqing Fu , Chen Bai , Ziyao Lin , Cheng Lu

Night images suffer not only from low light, but also from uneven distributions of light. Most existing night visibility enhancement methods focus mainly on enhancing low-light regions. This inevitably leads to over enhancement and…

Computer Vision and Pattern Recognition · Computer Science 2022-09-20 Yeying Jin , Wenhan Yang , Robby T. Tan

Recent advances in generative AI have dramatically improved image and video synthesis capabilities, significantly increasing the risk of misinformation through sophisticated fake content. In response, detection methods have evolved from…

Computer Vision and Pattern Recognition · Computer Science 2026-01-07 Haiquan Wen , Tianxiao Li , Zhenglin Huang , Yiwei He , Guangliang Cheng

We present DrivingGaussian++, an efficient and effective framework for realistic reconstructing and controllable editing of surrounding dynamic autonomous driving scenes. DrivingGaussian++ models the static background using incremental 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-08-29 Yajiao Xiong , Xiaoyu Zhou , Yongtao Wan , Deqing Sun , Ming-Hsuan Yang

Diffusion methods have been proven to be very effective to generate images while conditioning on a text prompt. However, and although the quality of the generated images is unprecedented, these methods seem to struggle when trying to…

Computer Vision and Pattern Recognition · Computer Science 2023-02-07 Álvaro Barbero Jiménez

Layered image assets are widely used in real-world creative workflows, enabling non-destructive iteration and flexible re-composition. Recent advances in layered image generation and decomposition synthesize or recover layered…

Computer Vision and Pattern Recognition · Computer Science 2026-05-12 Ryugo Morita , Stanislav Frolov , Brian Bernhard Moser , Ko Watanabe , Riku Takahashi , Issey Sukeda , Andreas Dengel

We address the computational problem of novel human pose synthesis. Given an image of a person and a desired pose, we produce a depiction of that person in that pose, retaining the appearance of both the person and background. We present a…

Computer Vision and Pattern Recognition · Computer Science 2018-04-23 Guha Balakrishnan , Amy Zhao , Adrian V. Dalca , Fredo Durand , John Guttag

Visual effects (VFX) are essential visual enhancements fundamental to modern cinematic production. Although video generation models offer cost-efficient solutions for VFX production, current methods are constrained by per-effect LoRA…

Computer Vision and Pattern Recognition · Computer Science 2025-12-18 Fangyuan Mao , Aiming Hao , Jintao Chen , Dongxia Liu , Xiaokun Feng , Jiashu Zhu , Meiqi Wu , Chubin Chen , Jiahong Wu , Xiangxiang Chu

Alignment between real and virtual objects is a challenging task required for the deployment of Mixed Reality (MR) into manufacturing, medical, and construction applications. To face this challenge, a series of methods have been proposed.…

Human-Computer Interaction · Computer Science 2022-11-17 Alejandro Martin-Gomez , Alexander Winkler , Rafael de la Tijera Obert , Javad Fotouhi , Daniel Roth , Ulrich Eck , Nassir Navab