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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

Recent advancements in video generation have been greatly driven by video diffusion models, with camera motion control emerging as a crucial challenge in creating view-customized visual content. This paper introduces trajectory attention, a…

Computer Vision and Pattern Recognition · Computer Science 2024-12-02 Zeqi Xiao , Wenqi Ouyang , Yifan Zhou , Shuai Yang , Lei Yang , Jianlou Si , Xingang Pan

Text-to-video diffusion models have advanced video generation significantly. However, customizing these models to generate videos with tailored motions presents a substantial challenge. In specific, they encounter hurdles in (a) accurately…

Computer Vision and Pattern Recognition · Computer Science 2023-12-05 Hyeonho Jeong , Geon Yeong Park , Jong Chul Ye

This work presents ViGeo, a feed-forward foundation model for recovering spatially dense and temporally consistent geometry from video sequences. Built upon a plain transformer architecture without task-specific architectural modifications,…

Computer Vision and Pattern Recognition · Computer Science 2026-05-29 Zhu Yu , Jingnan Gao , Runmin Zhang , Lingteng Qiu , Zhengyi Zhao , Rui Peng , Yichao Yan , Kejie Qiu , Siyu Zhu , Si-Yuan Cao , Hui-Liang Shen

Current video generation models perform well at single-shot synthesis but struggle with multi-shot videos, facing critical challenges in maintaining character and background consistency across shots and flexibly generating videos of…

Computer Vision and Pattern Recognition · Computer Science 2025-12-15 Xiangyang Luo , Qingyu Li , Xiaokun Liu , Wenyu Qin , Miao Yang , Meng Wang , Pengfei Wan , Di Zhang , Kun Gai , Shao-Lun Huang

Video editing is an emerging task, in which most current methods adopt the pre-trained text-to-image (T2I) diffusion model to edit the source video in a zero-shot manner. Despite extensive efforts, maintaining the temporal consistency of…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Jiangshan Wang , Yue Ma , Jiayi Guo , Yicheng Xiao , Gao Huang , Xiu Li

Video frame interpolation aims to synthesize realistic intermediate frames between given endpoints while adhering to specific motion semantics. While recent generative models have improved visual fidelity, they predominantly operate in a…

Computer Vision and Pattern Recognition · Computer Science 2026-04-03 Lingyu Liu , Yaxiong Wang , Li Zhu , Zhedong Zheng

We present a novel approach to optimally retarget videos for varied displays with differing aspect ratios by preserving salient scene content discovered via eye tracking. Our algorithm performs editing with cut, pan and zoom operations by…

Computer Vision and Pattern Recognition · Computer Science 2018-07-10 Kranthi Kumar , Moneish Kumar , Vineet Gandhi , Ramanathan Subramanian

Video restoration (VR) aims to recover high-quality videos from degraded ones. Although recent zero-shot VR methods using pre-trained diffusion models (DMs) show good promise, they suffer from approximation errors during reverse diffusion…

Computer Vision and Pattern Recognition · Computer Science 2025-03-20 Hengkang Wang , Yang Liu , Huidong Liu , Chien-Chih Wang , Yanhui Guo , Hongdong Li , Bryan Wang , Ju Sun

The rapid advancement of diffusion models has greatly improved video synthesis, especially in controllable video generation, which is vital for applications like autonomous driving. Although DiT with 3D VAE has become a standard framework…

Computer Vision and Pattern Recognition · Computer Science 2025-07-28 Ruiyuan Gao , Kai Chen , Bo Xiao , Lanqing Hong , Zhenguo Li , Qiang Xu

Video-based human pose estimation models aim to address scenarios that cannot be effectively solved by static image models such as motion blur, out-of-focus and occlusion. Most existing approaches consist of two stages: detecting human…

Computer Vision and Pattern Recognition · Computer Science 2025-09-03 Zhihong Wei

Temporal consistency is critical in video prediction to ensure that outputs are coherent and free of artifacts. Traditional methods, such as temporal attention and 3D convolution, may struggle with significant object motion and may not…

Computer Vision and Pattern Recognition · Computer Science 2025-03-26 Zihang Lai , Andrea Vedaldi

Diffusion-based methods can generate realistic images and videos, but they struggle to edit existing objects in a video while preserving their appearance over time. This prevents diffusion models from being applied to natural video editing…

Computer Vision and Pattern Recognition · Computer Science 2023-08-21 Wenhao Chai , Xun Guo , Gaoang Wang , Yan Lu

We present ReDirector, a novel camera-controlled video retake generation method for dynamically captured variable-length videos. In particular, we rectify a common misuse of RoPE in previous works by aligning the spatiotemporal positions of…

Computer Vision and Pattern Recognition · Computer Science 2025-11-26 Byeongjun Park , Byung-Hoon Kim , Hyungjin Chung , Jong Chul Ye

Despite the typical inversion-then-editing paradigm using text-to-image (T2I) models has demonstrated promising results, directly extending it to text-to-video (T2V) models still suffers severe artifacts such as color flickering and content…

Computer Vision and Pattern Recognition · Computer Science 2025-03-20 Yukun Wang , Longguang Wang , Zhiyuan Ma , Qibin Hu , Kai Xu , Yulan Guo

Leveraging the generative ability of image diffusion models offers great potential for zero-shot video-to-video translation. The key lies in how to maintain temporal consistency across generated video frames by image diffusion models.…

Computer Vision and Pattern Recognition · Computer Science 2023-11-02 Yuxiang Bao , Di Qiu , Guoliang Kang , Baochang Zhang , Bo Jin , Kaiye Wang , Pengfei Yan

Real-world applications like video gaming and virtual reality often demand the ability to model 3D scenes that users can explore along custom camera trajectories. While significant progress has been made in generating 3D objects from text…

Computer Vision and Pattern Recognition · Computer Science 2025-06-05 Tianyu Huang , Wangguandong Zheng , Tengfei Wang , Yuhao Liu , Zhenwei Wang , Junta Wu , Jie Jiang , Hui Li , Rynson W. H. Lau , Wangmeng Zuo , Chunchao Guo

We propose MLV-Edit, a training-free, flow-based framework that address the unique challenges of minute-level video editing. While existing techniques excel in short-form video manipulation, scaling them to long-duration videos remains…

Computer Vision and Pattern Recognition · Computer Science 2026-03-04 Yangyi Cao , Yuanhang Li , Lan Chen , Qi Mao

Video frame interpolation (VFI) that leverages the bio-inspired event cameras as guidance has recently shown better performance and memory efficiency than the frame-based methods, thanks to the event cameras' advantages, such as high…

Computer Vision and Pattern Recognition · Computer Science 2025-05-07 Haoyue Liu , Jinghan Xu , Yi Chang , Hanyu Zhou , Haozhi Zhao , Lin Wang , Luxin Yan

Recent progress in diffusion-based video editing has shown remarkable potential for practical applications. However, these methods remain prohibitively expensive and challenging to deploy on mobile devices. In this study, we introduce a…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Adil Karjauv , Noor Fathima , Ioannis Lelekas , Fatih Porikli , Amir Ghodrati , Amirhossein Habibian