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Recent advances in deep generative models have shown promising potential in image inpanting, which refers to the task of predicting missing pixel values of an incomplete image using the known context. However, existing methods can be slow…

Computer Vision and Pattern Recognition · Computer Science 2018-03-29 Chao Yang , Yuhang Song , Xiaofeng Liu , Qingming Tang , C. -C. Jay Kuo

Text-conditioned diffusion models have emerged as powerful tools for high-quality video generation. However, enabling Interactive Video Generation (IVG), where users control motion elements such as object trajectory, remains challenging.…

Computer Vision and Pattern Recognition · Computer Science 2025-06-02 Ishaan Rawal , Suryansh Kumar

There is a growing interest in using generative adversarial networks (GANs) to produce image content that is indistinguishable from real images as judged by a typical person. A number of GAN variants for this purpose have been proposed,…

Computer Vision and Pattern Recognition · Computer Science 2019-09-16 Zhengwei Wang , Graham Healy , Alan F. Smeaton , Tomas E. Ward

People with visual impairments often struggle to create content that relies heavily on visual elements, particularly when conveying spatial and structural information. Existing accessible drawing tools, which construct images line by line,…

Human-Computer Interaction · Computer Science 2025-04-30 Seonghee Lee , Maho Kohga , Steve Landau , Sile O'Modhrain , Hari Subramonyam

Recent deep learning based approaches have shown promising results for the challenging task of inpainting large missing regions in an image. These methods can generate visually plausible image structures and textures, but often create…

Computer Vision and Pattern Recognition · Computer Science 2018-03-23 Jiahui Yu , Zhe Lin , Jimei Yang , Xiaohui Shen , Xin Lu , Thomas S. Huang

Understanding and modeling the dynamics of human gaze behavior in 360$^\circ$ environments is a key challenge in computer vision and virtual reality. Generative adversarial approaches could alleviate this challenge by generating a large…

Computer Vision and Pattern Recognition · Computer Science 2024-05-22 Daniel Martin , Ana Serrano , Alexander W. Bergman , Gordon Wetzstein , Belen Masia

Recent approaches to controllable 4D video generation often rely on fine-tuning pre-trained Video Diffusion Models (VDMs). This dominant paradigm is computationally expensive, requiring large-scale datasets and architectural modifications,…

Computer Vision and Pattern Recognition · Computer Science 2025-12-08 Yeobin Hong , Suhyeon Lee , Hyungjin Chung , Jong Chul Ye

Gaussian Splatting has emerged as a leading method for novel view synthesis, offering superior training efficiency and real-time inference compared to NeRF approaches, while still delivering high-quality reconstructions. Beyond view…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Lorenzo Rutayisire , Nicola Capodieci , Fabio Pellacini

Generating high-fidelity landscape paintings remains a challenging task that requires precise control over both structure and style. In this paper, we present LPGen, a novel diffusion-based model specifically designed for landscape painting…

Computer Vision and Pattern Recognition · Computer Science 2024-10-14 Wanggong Yang , Yifei Zhao

Oil painting, as a high-level medium that blends human abstract thinking with artistic expression, poses substantial challenges for digital generation and editing due to its intricate brushstroke dynamics and stylized characteristics.…

Computer Vision and Pattern Recognition · Computer Science 2025-12-10 Zhangli Hu , Ye Chen , Jiajun Yao , Bingbing Ni

In this study, we propose two novel input processing paradigms for novel view synthesis (NVS) methods based on layered scene representations that significantly improve their runtime without compromising quality. Our approach identifies and…

Computer Vision and Pattern Recognition · Computer Science 2023-12-27 Jonas Kohler , Nicolas Griffiths Sanchez , Luca Cavalli , Catherine Herold , Albert Pumarola , Alberto Garcia Garcia , Ali Thabet

Image inpainting is the task of filling-in missing regions of a damaged or incomplete image. In this work we tackle this problem not only by using the available visual data but also by incorporating image semantics through the use of…

Computer Vision and Pattern Recognition · Computer Science 2018-12-05 Patricia Vitoria , Joan Sintes , Coloma Ballester

We introduce a novel method for dynamic free-view synthesis of an ambient scenes from a monocular capture bringing a immersive quality to the viewing experience. Our method builds upon the recent advancements in 3D Gaussian Splatting (3DGS)…

Computer Vision and Pattern Recognition · Computer Science 2024-06-14 Meng-Li Shih , Jia-Bin Huang , Changil Kim , Rajvi Shah , Johannes Kopf , Chen Gao

We present a method, Neural Radiance Flow (NeRFlow),to learn a 4D spatial-temporal representation of a dynamic scene from a set of RGB images. Key to our approach is the use of a neural implicit representation that learns to capture the 3D…

Computer Vision and Pattern Recognition · Computer Science 2021-09-07 Yilun Du , Yinan Zhang , Hong-Xing Yu , Joshua B. Tenenbaum , Jiajun Wu

We introduce an inversion based method, denoted as IMAge-Guided model INvErsion (IMAGINE), to generate high-quality and diverse images from only a single training sample. We leverage the knowledge of image semantics from a pre-trained…

Computer Vision and Pattern Recognition · Computer Science 2021-04-14 Pei Wang , Yijun Li , Krishna Kumar Singh , Jingwan Lu , Nuno Vasconcelos

In this paper, we use deep neural networks for inverting face sketches to synthesize photorealistic face images. We first construct a semi-simulated dataset containing a very large number of computer-generated face sketches with different…

Computer Vision and Pattern Recognition · Computer Science 2016-10-25 Yağmur Güçlütürk , Umut Güçlü , Rob van Lier , Marcel A. J. van Gerven

Generative Adversarial Networks (GANs) with style-based generators (e.g. StyleGAN) successfully enable semantic control over image synthesis, and recent studies have also revealed that interpretable image translations could be obtained by…

Computer Vision and Pattern Recognition · Computer Science 2020-11-20 Yunfan Liu , Qi Li , Zhenan Sun , Tieniu Tan

Design is a non-linear, reflective process in which practitioners engage with visual, semantic, and other expressive materials to explore, iterate, and refine ideas. As Generative AI (GenAI) becomes integrated into professional design…

Human-Computer Interaction · Computer Science 2026-03-04 Xiaohan Peng , Wendy E. Mackay , Janin Koch

Video inpainting aims to fill spatio-temporal "corrupted" regions with plausible content. To achieve this goal, it is necessary to find correspondences from neighbouring frames to faithfully hallucinate the unknown content. Current methods…

Computer Vision and Pattern Recognition · Computer Science 2021-04-09 Xueyan Zou , Linjie Yang , Ding Liu , Yong Jae Lee

Synthesizing realistic images from human drawn sketches is a challenging problem in computer graphics and vision. Existing approaches either need exact edge maps, or rely on retrieval of existing photographs. In this work, we propose a…

Computer Vision and Pattern Recognition · Computer Science 2018-04-16 Wengling Chen , James Hays
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