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Most approaches for video frame interpolation require accurate dense correspondences to synthesize an in-between frame. Therefore, they do not perform well in challenging scenarios with e.g. lighting changes or motion blur. Recent deep…

Computer Vision and Pattern Recognition · Computer Science 2018-04-04 Simone Meyer , Abdelaziz Djelouah , Brian McWilliams , Alexander Sorkine-Hornung , Markus Gross , Christopher Schroers

As neuromorphic sensors, event cameras asynchronously record changes in brightness as streams of sparse events with the advantages of high temporal resolution and high dynamic range. Reconstructing intensity images from events is a highly…

Computer Vision and Pattern Recognition · Computer Science 2025-11-24 Weilun Li , Lei Sun , Ruixi Gao , Qi Jiang , Yuqin Ma , Kaiwei Wang , Ming-Hsuan Yang , Luc Van Gool , Danda Pani Paudel

Video frame interpolation aims to generate high-quality intermediate frames from boundary frames and increase frame rate. While existing linear, symmetric and nonlinear models are used to bridge the gap from the lack of inter-frame motion,…

Computer Vision and Pattern Recognition · Computer Science 2023-05-19 Chenyang Shi , Hanxiao Liu , Jing Jin , Wenzhuo Li , Yuzhen Li , Boyi Wei , Yibo Zhang

Video Frame Interpolation (VFI) aims to synthesize intermediate frames between existing frames to enhance visual smoothness and quality. Beyond the conventional methods based on the reconstruction loss, recent works have employed generative…

Computer Vision and Pattern Recognition · Computer Science 2024-12-20 Jaihyun Lew , Jooyoung Choi , Chaehun Shin , Dahuin Jung , Sungroh Yoon

Video frame interpolation, which aims to synthesize non-exist intermediate frames in a video sequence, is an important research topic in computer vision. Existing video frame interpolation methods have achieved remarkable results under…

Computer Vision and Pattern Recognition · Computer Science 2021-12-03 Youjian Zhang , Chaoyue Wang , Dacheng Tao

Event cameras excel at high-speed, low-power, and high-dynamic-range scene perception. However, as they fundamentally record only relative intensity changes rather than absolute intensity, the resulting data streams suffer from a…

Computer Vision and Pattern Recognition · Computer Science 2026-05-08 Gang Xu , Zhiyu Zhu , Junhui Hou

Text-based diffusion models have exhibited remarkable success in generation and editing, showing great promise for enhancing visual content with their generative prior. However, applying these models to video super-resolution remains…

Computer Vision and Pattern Recognition · Computer Science 2023-12-12 Shangchen Zhou , Peiqing Yang , Jianyi Wang , Yihang Luo , Chen Change Loy

In this work, we propose a new diffusion-based method for video frame interpolation (VFI), in the context of traditional hand-made animation. We introduce three main contributions: The first is that we explicitly handle the interpolation…

Computer Vision and Pattern Recognition · Computer Science 2025-04-17 Victor Fonte Chavez , Claudia Esteves , Jean-Bernard Hayet

Text-driven image and video diffusion models have recently achieved unprecedented generation realism. While diffusion models have been successfully applied for image editing, very few works have done so for video editing. We present the…

Computer Vision and Pattern Recognition · Computer Science 2023-02-03 Eyal Molad , Eliahu Horwitz , Dani Valevski , Alex Rav Acha , Yossi Matias , Yael Pritch , Yaniv Leviathan , Yedid Hoshen

Diffusion models have achieved remarkable success in video generation; however, the high computational cost of the denoising process remains a major bottleneck. Existing approaches have shown promise in reducing the number of diffusion…

Computer Vision and Pattern Recognition · Computer Science 2026-02-03 Xiao Liang , Yunzhu Zhang , Linchao Zhu

Video interpolation aims to generate a non-existent intermediate frame given the past and future frames. Many state-of-the-art methods achieve promising results by estimating the optical flow between the known frames and then generating the…

Computer Vision and Pattern Recognition · Computer Science 2021-04-06 Zhiqi Chen , Ran Wang , Haojie Liu , Yao Wang

Video generation has achieved remarkable progress with the introduction of diffusion models, which have significantly improved the quality of generated videos. However, recent research has primarily focused on scaling up model training,…

Computer Vision and Pattern Recognition · Computer Science 2025-01-16 Chenyang Si , Weichen Fan , Zhengyao Lv , Ziqi Huang , Yu Qiao , Ziwei Liu

Despite advances in neural rendering, due to the scarcity of high-quality 3D datasets and the inherent limitations of multi-view diffusion models, view synthesis and 3D model generation are restricted to low resolutions with suboptimal…

Computer Vision and Pattern Recognition · Computer Science 2025-04-30 Yihang Luo , Shangchen Zhou , Yushi Lan , Xingang Pan , Chen Change Loy

Video inpainting has been challenged by complex scenarios like large movements and low-light conditions. Current methods, including emerging diffusion models, face limitations in quality and efficiency. This paper introduces the Flow-Guided…

Computer Vision and Pattern Recognition · Computer Science 2025-01-24 Bohai Gu , Yongsheng Yu , Heng Fan , Libo Zhang

In recent years, video generation has seen significant advancements. However, challenges still persist in generating complex motions and interactions. To address these challenges, we introduce ReVision, a plug-and-play framework that…

Computer Vision and Pattern Recognition · Computer Science 2026-01-12 Qihao Liu , Ju He , Qihang Yu , Liang-Chieh Chen , Alan Yuille

Event cameras, mimicking the human retina, capture brightness changes with unparalleled temporal resolution and dynamic range. Integrating events into intensities poses a highly ill-posed challenge, marred by initial condition ambiguities.…

Computer Vision and Pattern Recognition · Computer Science 2024-07-12 Jinxiu Liang , Bohan Yu , Yixin Yang , Yiming Han , Boxin Shi

Video post-processing methods can improve the quality of compressed videos at the decoder side. Most of the existing methods need to train corresponding models for compressed videos with different quantization parameters to improve the…

Image and Video Processing · Electrical Eng. & Systems 2023-11-16 Zheng Liu , Honggang Qi

Inspired by the impressive performance of recent face image editing methods, several studies have been naturally proposed to extend these methods to the face video editing task. One of the main challenges here is temporal consistency among…

Computer Vision and Pattern Recognition · Computer Science 2023-03-28 Gyeongman Kim , Hajin Shim , Hyunsu Kim , Yunjey Choi , Junho Kim , Eunho Yang

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

While AI-generated content has garnered significant attention, achieving photo-realistic video synthesis remains a formidable challenge. Despite the promising advances in diffusion models for video generation quality, the complex model…

Computer Vision and Pattern Recognition · Computer Science 2024-06-04 Zhengang Li , Yan Kang , Yuchen Liu , Difan Liu , Tobias Hinz , Feng Liu , Yanzhi Wang