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Perpetual view generation aims to synthesize a long-term video corresponding to an arbitrary camera trajectory solely from a single input image. Recent methods commonly utilize a pre-trained text-to-image diffusion model to synthesize new…

Computer Vision and Pattern Recognition · Computer Science 2025-06-24 Bo Pan , Yang Chen , Yingwei Pan , Ting Yao , Wei Chen , Tao Mei

This paper addresses the problem of reconstructing missing or dropped frames in top-down drone video of autonomous surface vehicles performing structured maritime manoeuvres. We propose a pipeline that converts raw GPS telemetry and a…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Stelio Bompai , Ioannis Kontopoulos , Giannis Spiliopoulos , Dimitris Zissis , Konstantinos Tserpes

Audio-driven cospeech video generation typically involves two stages: speech-to-gesture and gesture-to-video. While significant advances have been made in speech-to-gesture generation, synthesizing natural expressions and gestures remains…

Computer Vision and Pattern Recognition · Computer Science 2025-04-14 Renda Li , Xiaohua Qi , Qiang Ling , Jun Yu , Ziyi Chen , Peng Chang , Mei HanJing Xiao

Video generation with controllable camera viewpoints is essential for applications such as interactive content creation, gaming, and simulation. Existing methods typically adapt pre-trained video models using camera poses relative to a…

Computer Vision and Pattern Recognition · Computer Science 2026-02-10 Chunyang Li , Yuanbo Yang , Jiahao Shao , Hongyu Zhou , Katja Schwarz , Yiyi Liao

Synthesizing synchronized and natural co-speech gesture videos remains a formidable challenge. Recent approaches have leveraged motion graphs to harness the potential of existing video data. To retrieve an appropriate trajectory from the…

Computer Vision and Pattern Recognition · Computer Science 2025-12-03 Yafei Song , Peng Zhang , Bang Zhang

Building on the momentum of image generation diffusion models, there is an increasing interest in video-based diffusion models. However, video generation poses greater challenges due to its higher-dimensional nature, the scarcity of…

Computer Vision and Pattern Recognition · Computer Science 2024-11-01 Aimon Rahman , Malsha V. Perera , Vishal M. Patel

Volumetric video relighting is essential for bringing captured performances into virtual worlds, but current approaches struggle to deliver temporally stable, production-ready results. Diffusion-based intrinsic decomposition methods show…

Computer Vision and Pattern Recognition · Computer Science 2026-01-23 Elisabeth Jüttner , Janelle Pfeifer , Leona Krath , Stefan Korfhage , Hannah Dröge , Matthias B. Hullin , Markus Plack

A recent frontier in computer vision has been the task of 3D video generation, which consists of generating a time-varying 3D representation of a scene. To generate dynamic 3D scenes, current methods explicitly model 3D temporal dynamics by…

Computer Vision and Pattern Recognition · Computer Science 2024-08-01 Rishab Parthasarathy , Zachary Ankner , Aaron Gokaslan

In this work, we enhance a professional end-to-end volumetric video production pipeline to achieve high-fidelity human body reconstruction using only passive cameras. While current volumetric video approaches estimate depth maps using…

Computer Vision and Pattern Recognition · Computer Science 2022-03-01 Decai Chen , Markus Worchel , Ingo Feldmann , Oliver Schreer , Peter Eisert

The astonishing growth of generative tools in recent years has empowered many exciting applications in text-to-image generation and text-to-video generation. The underlying principle behind these generative tools is the concept of…

Machine Learning · Computer Science 2025-01-09 Stanley H. Chan

The ability to generate virtual environments is crucial for applications ranging from gaming to physical AI domains such as robotics, autonomous driving, and industrial AI. Current learning-based 3D reconstruction methods rely on the…

Computer Vision and Pattern Recognition · Computer Science 2025-09-24 Sherwin Bahmani , Tianchang Shen , Jiawei Ren , Jiahui Huang , Yifeng Jiang , Haithem Turki , Andrea Tagliasacchi , David B. Lindell , Zan Gojcic , Sanja Fidler , Huan Ling , Jun Gao , Xuanchi Ren

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

Recent text-to-video generation approaches rely on computationally heavy training and require large-scale video datasets. In this paper, we introduce a new task of zero-shot text-to-video generation and propose a low-cost approach (without…

Computer Vision and Pattern Recognition · Computer Science 2023-03-24 Levon Khachatryan , Andranik Movsisyan , Vahram Tadevosyan , Roberto Henschel , Zhangyang Wang , Shant Navasardyan , Humphrey Shi

Recent progress in generative diffusion models has greatly advanced text-to-video generation. While text-to-video models trained on large-scale, diverse datasets can produce varied outputs, these generations often deviate from user…

Computer Vision and Pattern Recognition · Computer Science 2024-12-19 Runtao Liu , Haoyu Wu , Zheng Ziqiang , Chen Wei , Yingqing He , Renjie Pi , Qifeng Chen

Diffusion models have revolutionized generative modeling, enabling unprecedented realism in image and video synthesis. This success has sparked interest in leveraging their representations for visual understanding tasks. While recent works…

Computer Vision and Pattern Recognition · Computer Science 2025-03-21 Pedro Vélez , Luisa F. Polanía , Yi Yang , Chuhan Zhang , Rishabh Kabra , Anurag Arnab , Mehdi S. M. Sajjadi

The remarkable generative capabilities of diffusion models have motivated extensive research in both image and video editing. Compared to video editing which faces additional challenges in the time dimension, image editing has witnessed the…

Computer Vision and Pattern Recognition · Computer Science 2024-05-28 Wenqi Ouyang , Yi Dong , Lei Yang , Jianlou Si , Xingang Pan

Computer-assisted interventions can improve intra-operative guidance, particularly through deep learning methods that harness the spatiotemporal information in surgical videos. However, the severe data imbalance often found in surgical…

Computer Vision and Pattern Recognition · Computer Science 2025-05-16 Danush Kumar Venkatesh , Isabel Funke , Micha Pfeiffer , Fiona Kolbinger , Hanna Maria Schmeiser , Juergen Weitz , Marius Distler , Stefanie Speidel

Are we ready to segment consumer stereo videos? The amount of this data type is rapidly increasing and encompasses rich information of appearance, motion and depth cues. However, the segmentation of such data is still largely unexplored.…

Computer Vision and Pattern Recognition · Computer Science 2016-09-08 Wei-Chen Chiu , Fabio Galasso , Mario Fritz

Diffusion models have demonstrated great success in text-to-video (T2V) generation. However, existing methods may face challenges when handling complex (long) video generation scenarios that involve multiple objects or dynamic changes in…

Computer Vision and Pattern Recognition · Computer Science 2024-10-15 Ye Tian , Ling Yang , Haotian Yang , Yuan Gao , Yufan Deng , Jingmin Chen , Xintao Wang , Zhaochen Yu , Xin Tao , Pengfei Wan , Di Zhang , Bin Cui

Whether to attract viewer attention to a particular object, give the impression of depth or simply reproduce human-like scene perception, shallow depth of field images are used extensively by professional and amateur photographers alike. To…

Computer Vision and Pattern Recognition · Computer Science 2019-10-01 Benjamin Busam , Matthieu Hog , Steven McDonagh , Gregory Slabaugh
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