English
Related papers

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

200 papers

This study introduces an efficient and effective method, MeDM, that utilizes pre-trained image Diffusion Models for video-to-video translation with consistent temporal flow. The proposed framework can render videos from scene position…

Computer Vision and Pattern Recognition · Computer Science 2023-12-21 Ernie Chu , Tzuhsuan Huang , Shuo-Yen Lin , Jun-Cheng Chen

Video Frame Interpolation (VFI) aims to generate intermediate video frames between consecutive input frames. Since the event cameras are bio-inspired sensors that only encode brightness changes with a micro-second temporal resolution,…

Computer Vision and Pattern Recognition · Computer Science 2025-02-20 Taewoo Kim , Yujeong Chae , Hyun-Kurl Jang , Kuk-Jin Yoon

Video inbetweening aims to synthesize intermediate video sequences conditioned on the given start and end frames. Current state-of-the-art methods primarily extend large-scale pre-trained Image-to-Video Diffusion Models (I2V-DMs) by…

Computer Vision and Pattern Recognition · Computer Science 2025-08-12 Liuhan Chen , Xiaodong Cun , Xiaoyu Li , Xianyi He , Shenghai Yuan , Jie Chen , Ying Shan , Li Yuan

Fast neuromorphic event-based vision sensors (Dynamic Vision Sensor, DVS) can be combined with slower conventional frame-based sensors to enable higher-quality inter-frame interpolation than traditional methods relying on fixed motion…

Computer Vision and Pattern Recognition · Computer Science 2021-12-20 Adam Radomski , Andreas Georgiou , Thomas Debrunner , Chenghan Li , Luca Longinotti , Minwon Seo , Moosung Kwak , Chang-Woo Shin , Paul K. J. Park , Hyunsurk Eric Ryu , Kynan Eng

Face reenactment aims to generate realistic talking head videos by transferring motion from a driving video to a static source image while preserving the source identity. Although existing methods based on either implicit or explicit…

Computer Vision and Pattern Recognition · Computer Science 2025-07-23 Mingtao Guo , Guanyu Xing , Yanci Zhang , Yanli Liu

Every generation of mobile devices strives to capture video at higher resolution and frame rate than previous ones. This quality increase also requires additional power and computation to capture and encode high-quality media. We propose a…

Image and Video Processing · Electrical Eng. & Systems 2025-03-31 Hidekazu Takahashi , Takefumi Nagumo , Kensei Jo , Aumiller Andreas , Saeed Rad , Rodrigo Caye Daudt , Yoshitaka Miyatani , Hayato Wakabayashi , Christian Brandli

State-of-the-art text-to-video models often look realistic frame-by-frame yet fail on simple interactions: motion starts before contact, actions are not realized, objects drift after placement, and support relations break. We argue this…

Computer Vision and Pattern Recognition · Computer Science 2026-03-19 Chika Maduabuchi

Predicting and anticipating future outcomes or reasoning about missing information in a sequence are critical skills for agents to be able to make intelligent decisions. This requires strong, temporally coherent generative capabilities.…

Computer Vision and Pattern Recognition · Computer Science 2022-11-15 Tobias Höppe , Arash Mehrjou , Stefan Bauer , Didrik Nielsen , Andrea Dittadi

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

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 (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 prediction is a challenging task. The quality of video frames from current state-of-the-art (SOTA) generative models tends to be poor and generalization beyond the training data is difficult. Furthermore, existing prediction…

Computer Vision and Pattern Recognition · Computer Science 2022-10-14 Vikram Voleti , Alexia Jolicoeur-Martineau , Christopher Pal

The stereo event-intensity camera setup is widely applied to leverage the advantages of both event cameras with low latency and intensity cameras that capture accurate brightness and texture information. However, such a setup commonly…

Computer Vision and Pattern Recognition · Computer Science 2023-07-18 Chao Ding , Mingyuan Lin , Haijian Zhang , Jianzhuang Liu , Lei Yu

Recent advancements in diffusion models have significantly facilitated text-guided video editing. However, there is a relative scarcity of research on image-guided video editing, a method that empowers users to edit videos by merely…

Computer Vision and Pattern Recognition · Computer Science 2025-01-09 Zhi-Lin Huang , Yixuan Liu , Chujun Qin , Zhongdao Wang , Dong Zhou , Dong Li , Emad Barsoum

Current optical flow methods exploit the stable appearance of frame (or RGB) data to establish robust correspondences across time. Event cameras, on the other hand, provide high-temporal-resolution motion cues and excel in challenging…

Computer Vision and Pattern Recognition · Computer Science 2025-08-20 Qianang Zhou , Junhui Hou , Meiyi Yang , Yongjian Deng , Youfu Li , Junlin Xiong

Event-based video reconstruction has garnered increasing attention due to its advantages, such as high dynamic range and rapid motion capture capabilities. However, current methods often prioritize the extraction of temporal information…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Lin Zhu , Yunlong Zheng , Yijun Zhang , Xiao Wang , Lizhi Wang , Hua Huang

Recent advancements in diffusion models have set new benchmarks in image and video generation, enabling realistic visual synthesis across single- and multi-frame contexts. However, these models still struggle with efficiently and explicitly…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Qihang Zhang , Shuangfei Zhai , Miguel Angel Bautista , Kevin Miao , Alexander Toshev , Joshua Susskind , Jiatao Gu

In challenging low light and adverse weather conditions,thermal vision algorithms,especially object detection,have exhibited remarkable potential,contrasting with the frequent struggles encountered by visible vision algorithms.…

Computer Vision and Pattern Recognition · Computer Science 2024-08-08 Guoqing Zhu , Honghu Pan , Qiang Wang , Chao Tian , Chao Yang , Zhenyu He

Continuous video monitoring in surveillance, robotics, and wearable systems faces a fundamental power constraint: conventional RGB cameras consume substantial energy through fixed-rate capture. Event cameras offer sparse, motion-driven…

Computer Vision and Pattern Recognition · Computer Science 2025-12-08 Dmitrii Torbunov , Onur Okuducu , Yi Huang , Odera Dim , Rebecca Coles , Yonggang Cui , Yihui Ren

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