English
Related papers

Related papers: ViBiDSampler: Enhancing Video Interpolation Using …

200 papers

We present a diffusion-based image morphing approach with perceptually-uniform sampling (IMPUS) that produces smooth, direct and realistic interpolations given an image pair. The embeddings of two images may lie on distinct conditioned…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Zhaoyuan Yang , Zhengyang Yu , Zhiwei Xu , Jaskirat Singh , Jing Zhang , Dylan Campbell , Peter Tu , Richard Hartley

Video frame interpolation is a challenging problem because there are different scenarios for each video depending on the variety of foreground and background motion, frame rate, and occlusion. It is therefore difficult for a single network…

Computer Vision and Pattern Recognition · Computer Science 2020-04-03 Myungsub Choi , Janghoon Choi , Sungyong Baik , Tae Hyun Kim , Kyoung Mu Lee

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

Imagining multiple consecutive frames given one single snapshot is challenging, since it is difficult to simultaneously predict diverse motions from a single image and faithfully generate novel frames without visual distortions. In this…

Computer Vision and Pattern Recognition · Computer Science 2019-03-05 Lu Sheng , Junting Pan , Jiaming Guo , Jing Shao , Xiaogang Wang , Chen Change Loy

Video super-resolution (VSR) seeks to reconstruct high-resolution frames from low-resolution inputs. While diffusion-based methods have substantially improved perceptual quality, extending them to video remains challenging for two reasons:…

Computer Vision and Pattern Recognition · Computer Science 2026-03-30 Jintong Hu , Bin Chen , Zhenyu Hu , Jiayue Liu , Guo Wang , Lu Qi

Diffusion models have achieved remarkable success in image generation but their practical application is often hindered by the slow sampling speed. Prior efforts of improving efficiency primarily focus on compressing models or reducing the…

Computer Vision and Pattern Recognition · Computer Science 2026-03-16 Jiuyi Xu , Qing Jin , Meida Chen , Andrew Feng , Yang Sui , Yangming Shi

We pose a new problem, In-2-4D, for generative 4D (i.e., 3D + motion) inbetweening to interpolate two single-view images. In contrast to video/4D generation from only text or a single image, our interpolative task can leverage more precise…

Graphics · Computer Science 2025-09-30 Sauradip Nag , Daniel Cohen-Or , Hao Zhang , Ali Mahdavi-Amiri

Video frame interpolation methodologies endeavor to create novel frames betwixt extant ones, with the intent of augmenting the video's frame frequency. However, current methods are prone to image blurring and spurious artifacts in…

Computer Vision and Pattern Recognition · Computer Science 2024-02-06 Pengfei Han , Fuhua Zhang , Bin Zhao , Xuelong Li

Generating multiview images from a single view facilitates the rapid generation of a 3D mesh conditioned on a single image. Recent methods that introduce 3D global representation into diffusion models have shown the potential to generate…

Computer Vision and Pattern Recognition · Computer Science 2024-04-03 Zehuan Huang , Hao Wen , Junting Dong , Yaohui Wang , Yangguang Li , Xinyuan Chen , Yan-Pei Cao , Ding Liang , Yu Qiao , Bo Dai , Lu Sheng

Stable Diffusion (SD) has evolved DDPM (Denoising Diffusion Probabilistic Model) based image generation significantly by denoising in latent space instead of feature space. This popularized DDPM-based image generation as the cost and…

Computer Vision and Pattern Recognition · Computer Science 2026-05-15 Md Abu Obaida Zishan , Jannatun Noor , Annajiat Alim Rasel

Video frame interpolation is one of the most challenging tasks in video processing research. Recently, many studies based on deep learning have been suggested. Most of these methods focus on finding locations with useful information to…

Computer Vision and Pattern Recognition · Computer Science 2020-03-10 Hyeongmin Lee , Taeoh Kim , Tae-young Chung , Daehyun Pak , Yuseok Ban , Sangyoun Lee

In this paper, we firstly present a dataset (X4K1000FPS) of 4K videos of 1000 fps with the extreme motion to the research community for video frame interpolation (VFI), and propose an extreme VFI network, called XVFI-Net, that first handles…

Computer Vision and Pattern Recognition · Computer Science 2021-08-06 Hyeonjun Sim , Jihyong Oh , Munchurl Kim

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

Inter-frame modeling is pivotal in generating intermediate frames for video frame interpolation (VFI). Current approaches predominantly rely on convolution or attention-based models, which often either lack sufficient receptive fields or…

Computer Vision and Pattern Recognition · Computer Science 2024-10-11 Guozhen Zhang , Chunxu Liu , Yutao Cui , Xiaotong Zhao , Kai Ma , Limin Wang

Diffusion Transformer (DiT)-based video diffusion models generate high-quality videos at scale but incur prohibitive processing latency and memory costs for long videos. To address this, we propose a novel distributed inference strategy,…

Computer Vision and Pattern Recognition · Computer Science 2025-05-30 Zeqing Wang , Bowen Zheng , Xingyi Yang , Zhenxiong Tan , Yuecong Xu , Xinchao Wang

Despite recent successes in novel view synthesis using 3D Gaussian Splatting (3DGS), modeling scenes with sparse inputs remains a challenge. In this work, we address two critical yet overlooked issues in real-world sparse-input modeling:…

Computer Vision and Pattern Recognition · Computer Science 2025-03-10 Yingji Zhong , Zhihao Li , Dave Zhenyu Chen , Lanqing Hong , Dan Xu

Diffusion models have achieved remarkable progress on image-to-video (I2V) generation, while their noise-to-data generation process is inherently mismatched with this task, which may lead to suboptimal synthesis quality. In this work, we…

Computer Vision and Pattern Recognition · Computer Science 2025-06-17 Yuji Wang , Zehua Chen , Xiaoyu Chen , Yixiang Wei , Jun Zhu , Jianfei Chen

Recent advancements have integrated camera pose as a user-friendly and physics-informed condition in video diffusion models, enabling precise camera control. In this paper, we identify one of the key challenges as effectively modeling noisy…

Computer Vision and Pattern Recognition · Computer Science 2024-12-05 Guangcong Zheng , Teng Li , Rui Jiang , Yehao Lu , Tao Wu , Xi Li

In this paper, we propose VistaDream a novel framework to reconstruct a 3D scene from a single-view image. Recent diffusion models enable generating high-quality novel-view images from a single-view input image. Most existing methods only…

Computer Vision and Pattern Recognition · Computer Science 2024-10-23 Haiping Wang , Yuan Liu , Ziwei Liu , Wenping Wang , Zhen Dong , Bisheng Yang

With the emergence of diffusion models and rapid development in image processing, it has become effortless to generate fancy images in tasks such as style transfer and image editing. However, these impressive image processing approaches…

Computer Vision and Pattern Recognition · Computer Science 2023-11-17 Zhongjie Duan , Chengyu Wang , Cen Chen , Weining Qian , Jun Huang , Mingyi Jin