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Related papers: EGVD: Event-Guided Video Diffusion Model for Physi…

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We introduce the Joint Video-Image Diffusion model (JVID), a novel approach to generating high-quality and temporally coherent videos. We achieve this by integrating two diffusion models: a Latent Image Diffusion Model (LIDM) trained on…

Computer Vision and Pattern Recognition · Computer Science 2024-09-30 Hadrien Reynaud , Matthew Baugh , Mischa Dombrowski , Sarah Cechnicka , Qingjie Meng , Bernhard Kainz

Utilization of event-based cameras is expected to improve the visual quality of video frame interpolation solutions. We introduce a learning-based method to exploit moving region boundaries in a video sequence to increase the overall…

Image and Video Processing · Electrical Eng. & Systems 2023-03-06 Ahmet Akman , Onur Selim Kılıç , A. Aydın Alatan

Event cameras offer various advantages for novel view rendering compared to synchronously operating RGB cameras, and efficient event-based techniques supporting rigid scenes have been recently demonstrated in the literature. In the case of…

Computer Vision and Pattern Recognition · Computer Science 2025-10-14 Takuya Nakabayashi , Navami Kairanda , Hideo Saito , Vladislav Golyanik

Reliable seizure detection in mouse models is essential for preclinical epilepsy research, yet manual review of synchronized video-EEG recordings is labor-intensive and single-modality systems fail for complementary reasons: video-based…

Computer Vision and Pattern Recognition · Computer Science 2026-04-30 Tong Lu , Ke Xu , Zimo Zhang , Zitong Zhao , Danwei Weng , Ruiyu Wang , Miao Liu , Zizuo Zhang , Jingyi Yao , Yixuan Zhao , Wenchao Zhang , Min Wang , Guoming Luan , Minmin Luo , Zhifeng Yue

Leveraging text, images, structure maps, or motion trajectories as conditional guidance, diffusion models have achieved great success in automated and high-quality video generation. However, generating smooth and rational transition videos…

Computer Vision and Pattern Recognition · Computer Science 2025-08-05 Zuhao Yang , Jiahui Zhang , Yingchen Yu , Shijian Lu , Song Bai

Despite the remarkable progress in deep generative models, synthesizing high-resolution and temporally coherent videos still remains a challenge due to their high-dimensionality and complex temporal dynamics along with large spatial…

Computer Vision and Pattern Recognition · Computer Science 2023-03-31 Sihyun Yu , Kihyuk Sohn , Subin Kim , Jinwoo Shin

State-of-the-art frame interpolation methods generate intermediate frames by inferring object motions in the image from consecutive key-frames. In the absence of additional information, first-order approximations, i.e. optical flow, must be…

Computer Vision and Pattern Recognition · Computer Science 2021-06-15 Stepan Tulyakov , Daniel Gehrig , Stamatios Georgoulis , Julius Erbach , Mathias Gehrig , Yuanyou Li , Davide Scaramuzza

Real-world low-resolution (LR) videos have diverse and complex degradations, imposing great challenges on video super-resolution (VSR) algorithms to reproduce their high-resolution (HR) counterparts with high quality. Recently, the…

Computer Vision and Pattern Recognition · Computer Science 2024-07-15 Xi Yang , Chenhang He , Jianqi Ma , Lei Zhang

Video frame interpolation (VFI) is a challenging task that aims to generate intermediate frames between two consecutive frames in a video. Existing learning-based VFI methods have achieved great success, but they still suffer from limited…

Computer Vision and Pattern Recognition · Computer Science 2023-10-06 Haoning Wu , Xiaoyun Zhang , Weidi Xie , Ya Zhang , Yanfeng Wang

Video frame interpolation (VFI) is the task that synthesizes the intermediate frame given two consecutive frames. Most of the previous studies have focused on appropriate frame warping operations and refinement modules for the warped…

Computer Vision and Pattern Recognition · Computer Science 2023-03-24 Sangjin Lee , Hyeongmin Lee , Chajin Shin , Hanbin Son , Sangyoun Lee

Most existing video anomaly detectors rely solely on RGB frames, which lack the temporal resolution needed to capture abrupt or transient motion cues, key indicators of anomalous events. To address this limitation, we propose Image-Event…

Computer Vision and Pattern Recognition · Computer Science 2025-05-09 Sungheon Jeong , Jihong Park , Mohsen Imani

Diffusion models, widely used in image generation, rely on iterative refinement to generate images from noise. Understanding this data evolution is important for model development and interpretability, yet challenging due to its…

Computer Vision and Pattern Recognition · Computer Science 2024-12-12 Vidya Prasad , Hans van Gorp , Christina Humer , Ruud J. G. van Sloun , Anna Vilanova , Nicola Pezzotti

Event-based cameras measure intensity changes (called `events') with microsecond accuracy under high-speed motion and challenging lighting conditions. With the `active pixel sensor' (APS), the `Dynamic and Active-pixel Vision Sensor'…

Computer Vision and Pattern Recognition · Computer Science 2020-11-13 Liyuan Pan , Richard Hartley , Cedric Scheerlinck , Miaomiao Liu , Xin Yu , Yuchao Dai

Effective video frame interpolation hinges on the adept handling of motion in the input scene. Prior work acknowledges asynchronous event information for this, but often overlooks whether motion induces blur in the video, limiting its scope…

Computer Vision and Pattern Recognition · Computer Science 2025-05-21 Lei Sun , Daniel Gehrig , Christos Sakaridis , Mathias Gehrig , Jingyun Liang , Peng Sun , Zhijie Xu , Kaiwei Wang , Luc Van Gool , Davide Scaramuzza

This paper addresses the novel challenge of ``rewinding'' time from a single captured image to recover the fleeting moments missed just before the shutter button is pressed. This problem poses a significant challenge in computer vision and…

Computer Vision and Pattern Recognition · Computer Science 2024-03-21 Jingxi Chen , Brandon Y. Feng , Haoming Cai , Mingyang Xie , Christopher Metzler , Cornelia Fermuller , Yiannis Aloimonos

Following the advancements in text-guided image generation technology exemplified by Stable Diffusion, video generation is gaining increased attention in the academic community. However, relying solely on text guidance for video generation…

Computer Vision and Pattern Recognition · Computer Science 2024-09-17 Cong Wang , Jiaxi Gu , Panwen Hu , Haoyu Zhao , Yuanfan Guo , Jianhua Han , Hang Xu , Xiaodan Liang

Temporally consistent video-to-video generation is critical for applications such as style transfer and upsampling. In this paper, we provide a theoretical analysis of warped noise - a recently proposed technique for training video…

Computer Vision and Pattern Recognition · Computer Science 2025-10-17 Chao Liu , Arash Vahdat

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

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

Video diffusion models have rapidly become the dominant paradigm for high-fidelity generative video synthesis, but their practical deployment remains constrained by severe inference costs. Compared with image generation, video synthesis…

Computer Vision and Pattern Recognition · Computer Science 2026-04-20 Shitong Shao , Lichen Bai , Pengfei Wan , James Kwok , Zeke Xie
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