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Video generation has made remarkable progress in recent years, especially since the advent of the video diffusion models. Many video generation models can produce plausible synthetic videos, e.g., Stable Video Diffusion (SVD). However, most…

Computer Vision and Pattern Recognition · Computer Science 2024-06-04 Shaoshu Yang , Yong Zhang , Xiaodong Cun , Ying Shan , Ran He

Video frame interpolation typically involves two steps: motion estimation and pixel synthesis. Such a two-step approach heavily depends on the quality of motion estimation. This paper presents a robust video frame interpolation method that…

Computer Vision and Pattern Recognition · Computer Science 2017-03-23 Simon Niklaus , Long Mai , Feng Liu

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

We propose a light-weight video frame interpolation algorithm. Our key innovation is an instance-level supervision that allows information to be learned from the high-resolution version of similar objects. Our experiment shows that the…

Computer Vision and Pattern Recognition · Computer Science 2019-04-30 Liangzhe Yuan , Yibo Chen , Hantian Liu , Tao Kong , Jianbo Shi

Diffusion models have achieved remarkable success in generating high quality image and video data. More recently, they have also been used for image compression with high perceptual quality. In this paper, we present a novel approach to…

Image and Video Processing · Electrical Eng. & Systems 2024-02-15 Bohan Li , Yiming Liu , Xueyan Niu , Bo Bai , Lei Deng , Deniz Gündüz

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 virtual try-on aims to transfer a clothing item onto the video of a target person. Directly applying the technique of image-based try-on to the video domain in a frame-wise manner will cause temporal-inconsistent outcomes while…

Computer Vision and Pattern Recognition · Computer Science 2024-05-29 Zixun Fang , Wei Zhai , Aimin Su , Hongliang Song , Kai Zhu , Mao Wang , Yu Chen , Zhiheng Liu , Yang Cao , Zheng-Jun Zha

Video frame interpolation is an important low-level vision task, which can increase frame rate for more fluent visual experience. Existing methods have achieved great success by employing advanced motion models and synthesis networks.…

Computer Vision and Pattern Recognition · Computer Science 2023-09-22 Lingtong Kong , Boyuan Jiang , Donghao Luo , Wenqing Chu , Ying Tai , Chengjie Wang , Jie Yang

Existing video frame interpolation (VFI) methods often adopt a frame-centric approach, processing videos as independent short segments (e.g., triplets), which leads to temporal inconsistencies and motion artifacts. To overcome this, we…

Computer Vision and Pattern Recognition · Computer Science 2026-03-31 Xinyu Peng , Han Li , Yuyang Huang , Ziyang Zheng , Yaoming Wang , Xin Chen , Wenrui Dai , Chenglin Li , Junni Zou , Hongkai Xiong

Video diffusion models have recently made great progress in generation quality, but are still limited by the high memory and computational requirements. This is because current video diffusion models often attempt to process…

Computer Vision and Pattern Recognition · Computer Science 2024-03-22 Sihyun Yu , Weili Nie , De-An Huang , Boyi Li , Jinwoo Shin , Anima Anandkumar

Generating temporally coherent high fidelity video is an important milestone in generative modeling research. We make progress towards this milestone by proposing a diffusion model for video generation that shows very promising initial…

Computer Vision and Pattern Recognition · Computer Science 2022-06-24 Jonathan Ho , Tim Salimans , Alexey Gritsenko , William Chan , Mohammad Norouzi , David J. Fleet

Diffusion models have emerged as a powerful paradigm in video synthesis tasks including prediction, generation, and interpolation. Due to the limitation of the computational budget, existing methods usually implement conditional diffusion…

Computer Vision and Pattern Recognition · Computer Science 2023-06-06 Siyuan Yang , Lu Zhang , Yu Liu , Zhizhuo Jiang , You He

Diffusion models have been widely used for conditional data cross-modal generation tasks such as text-to-image and text-to-video. However, state-of-the-art models still fail to align the generated visual concepts with high-level semantics…

Computer Vision and Pattern Recognition · Computer Science 2024-03-26 Zizhao Hu , Shaochong Jia , Mohammad Rostami

This paper considers an efficient video modeling process called Video Latent Flow Matching (VLFM). Unlike prior works, which randomly sampled latent patches for video generation, our method relies on current strong pre-trained image…

Computer Vision and Pattern Recognition · Computer Science 2025-02-05 Yang Cao , Zhao Song , Chiwun Yang

Text-guided image-to-video (I2V) generation aims to generate a coherent video that preserves the identity of the input image and semantically aligns with the input prompt. Existing methods typically augment pretrained text-to-video (T2V)…

Computer Vision and Pattern Recognition · Computer Science 2024-06-28 Xun Guo , Mingwu Zheng , Liang Hou , Yuan Gao , Yufan Deng , Pengfei Wan , Di Zhang , Yufan Liu , Weiming Hu , Zhengjun Zha , Haibin Huang , Chongyang Ma

Video Frame Interpolation (VFI) is a fundamental yet challenging task in computer vision, particularly under conditions involving large motion, occlusion, and lighting variation. Recent advancements in event cameras have opened up new…

Computer Vision and Pattern Recognition · Computer Science 2025-05-14 Hanle Zheng , Xujie Han , Zegang Peng , Shangbin Zhang , Guangxun Du , Zhuo Zou , Xilin Wang , Jibin Wu , Hao Guo , Lei Deng

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

Video frame interpolation (VFI) aims to synthesize an intermediate frame between two consecutive frames. State-of-the-art approaches usually adopt a two-step solution, which includes 1) generating locally-warped pixels by flow-based motion…

Computer Vision and Pattern Recognition · Computer Science 2022-07-20 Chengxu Liu , Huan Yang , Jianlong Fu , Xueming Qian

Given two consecutive frames, video interpolation aims at generating intermediate frame(s) to form both spatially and temporally coherent video sequences. While most existing methods focus on single-frame interpolation, we propose an…

Computer Vision and Pattern Recognition · Computer Science 2018-07-16 Huaizu Jiang , Deqing Sun , Varun Jampani , Ming-Hsuan Yang , Erik Learned-Miller , Jan Kautz

Recent advances in high refresh rate displays as well as the increased interest in high rate of slow motion and frame up-conversion fuel the demand for efficient and cost-effective multi-frame video interpolation solutions. To that regard,…

Computer Vision and Pattern Recognition · Computer Science 2021-01-12 Zhixiang Chi , Rasoul Mohammadi Nasiri , Zheng Liu , Juwei Lu , Jin Tang , Konstantinos N Plataniotis