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相关论文: StreamGVE: Training-Free Video Editing via Few-Ste…

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Streaming video effect generation is highly desirable for live human-centric applications such as e-commerce streaming, entertainment, and vlogging, yet remains difficult due to the lack of suitable data and deployable editing models.…

计算机视觉与模式识别 · 计算机科学 2026-05-19 Yiren Song , Cheng Liu , Yuxin Jiang , Mike Zheng Shou

Recently, great progress has been achieved in text-to-video (T2V) generation by scaling transformer-based diffusion models to billions of parameters, which can generate high-quality videos. However, existing models typically produce only…

计算机视觉与模式识别 · 计算机科学 2026-03-30 Akio Kodaira , Tingbo Hou , Ji Hou , Markos Georgopoulos , Felix Juefei-Xu , Masayoshi Tomizuka , Yue Zhao

Text-to-video diffusion models enable the generation of high-quality videos that follow text instructions, making it easy to create diverse and individual content. However, existing approaches mostly focus on high-quality short video…

计算机视觉与模式识别 · 计算机科学 2025-04-17 Roberto Henschel , Levon Khachatryan , Hayk Poghosyan , Daniil Hayrapetyan , Vahram Tadevosyan , Zhangyang Wang , Shant Navasardyan , Humphrey Shi

Recent advancements in diffusion-based models have demonstrated significant success in generating images from text. However, video editing models have not yet reached the same level of visual quality and user control. To address this, we…

计算机视觉与模式识别 · 计算机科学 2023-12-08 Ozgur Kara , Bariscan Kurtkaya , Hidir Yesiltepe , James M. Rehg , Pinar Yanardag

In the dynamic field of digital content creation using generative models, state-of-the-art video editing models still do not offer the level of quality and control that users desire. Previous works on video editing either extended from…

计算机视觉与模式识别 · 计算机科学 2024-11-05 Max Ku , Cong Wei , Weiming Ren , Harry Yang , Wenhu Chen

Generative models are reshaping the live-streaming industry by redefining how content is created, styled, and delivered. Previous image-based streaming diffusion models have powered efficient and creative live streaming products but have…

计算机视觉与模式识别 · 计算机科学 2026-02-24 Tianrui Feng , Zhi Li , Shuo Yang , Haocheng Xi , Muyang Li , Xiuyu Li , Lvmin Zhang , Keting Yang , Kelly Peng , Song Han , Maneesh Agrawala , Kurt Keutzer , Akio Kodaira , Chenfeng Xu

Video editing aims to modify input videos according to user intent. Recently, end-to-end training methods have garnered widespread attention, constructing paired video editing data through video generation or editing models. However,…

计算机视觉与模式识别 · 计算机科学 2026-04-21 Weicheng Wang , Zhicheng Zhang , Zhongqi Zhang , Juncheng Zhou , Yongjie Zhu , Wenyu Qin , Meng Wang , Pengfei Wan , Jufeng Yang

With the prosper of video diffusion models, down-stream applications like video editing have been significantly promoted without consuming much computational cost. One particular challenge in this task lies at the motion transfer process…

计算机视觉与模式识别 · 计算机科学 2025-06-16 Ge Wang , Songlin Fan , Hangxu Liu , Quanjian Song , Hewei Wang , Jinfeng Xu

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…

计算机视觉与模式识别 · 计算机科学 2023-03-24 Levon Khachatryan , Andranik Movsisyan , Vahram Tadevosyan , Roberto Henschel , Zhangyang Wang , Shant Navasardyan , Humphrey Shi

Instructional video generation is an emerging task that aims to synthesize coherent demonstrations of procedural activities from textual descriptions. Such capability has broad implications for content creation, education, and human-AI…

计算机视觉与模式识别 · 计算机科学 2025-12-16 Cheeun Hong , German Barquero , Fadime Sener , Markos Georgopoulos , Edgar Schönfeld , Stefan Popov , Yuming Du , Oscar Mañas , Albert Pumarola

Recent video diffusion models have enhanced video editing, but it remains challenging to handle instructional editing and diverse tasks (e.g., adding, removing, changing) within a unified framework. In this paper, we introduce VEGGIE, a…

计算机视觉与模式识别 · 计算机科学 2025-10-28 Shoubin Yu , Difan Liu , Ziqiao Ma , Yicong Hong , Yang Zhou , Hao Tan , Joyce Chai , Mohit Bansal

While image manipulation achieves tremendous breakthroughs (e.g., generating realistic faces) in recent years, video generation is much less explored and harder to control, which limits its applications in the real world. For instance,…

计算机视觉与模式识别 · 计算机科学 2019-08-08 Tsun-Hsuan Wang , Yen-Chi Cheng , Chieh Hubert Lin , Hwann-Tzong Chen , Min Sun

Instruction-based editing holds vast potential due to its simple and efficient interactive editing format. However, instruction-based editing, particularly for video, has been constrained by limited training data, hindering its practical…

计算机视觉与模式识别 · 计算机科学 2025-08-11 Bin Xia , Jiyang Liu , Yuechen Zhang , Bohao Peng , Ruihang Chu , Yitong Wang , Xinglong Wu , Bei Yu , Jiaya Jia

We introduce a novel diffusion-based video generation method, generating a video showing multiple events given multiple individual sentences from the user. Our method does not require a large-scale video dataset since our method uses a…

计算机视觉与模式识别 · 计算机科学 2024-07-17 Gyeongrok Oh , Jaehwan Jeong , Sieun Kim , Wonmin Byeon , Jinkyu Kim , Sungwoong Kim , Sangpil Kim

This paper introduces StreamV2V, a diffusion model that achieves real-time streaming video-to-video (V2V) translation with user prompts. Unlike prior V2V methods using batches to process limited frames, we opt to process frames in a…

计算机视觉与模式识别 · 计算机科学 2025-02-18 Feng Liang , Akio Kodaira , Chenfeng Xu , Masayoshi Tomizuka , Kurt Keutzer , Diana Marculescu

Image generative models have made significant progress in generating realistic and diverse images, supported by comprehensive guidance from various evaluation metrics. However, current video generative models struggle to generate even short…

计算机视觉与模式识别 · 计算机科学 2024-04-01 Pum Jun Kim , Seojun Kim , Jaejun Yoo

Video generation based on diffusion models presents a challenging multimodal task, with video editing emerging as a pivotal direction in this field. Recent video editing approaches primarily fall into two categories: training-required and…

计算机视觉与模式识别 · 计算机科学 2025-05-13 Junhao Xia , Chaoyang Zhang , Yecheng Zhang , Chengyang Zhou , Zhichang Wang , Bochun Liu , Dongshuo Yin

Transition videos play a crucial role in media production, enhancing the flow and coherence of visual narratives. Traditional methods like morphing often lack artistic appeal and require specialized skills, limiting their effectiveness.…

计算机视觉与模式识别 · 计算机科学 2024-08-27 Rui Zhang , Yaosen Chen , Yuegen Liu , Wei Wang , Xuming Wen , Hongxia Wang

Video streaming is a fundamental Internet service, while the quality still cannot be guaranteed especially in poor network conditions such as bandwidth-constrained and remote areas. Existing works mainly work towards two directions:…

网络与互联网体系结构 · 计算机科学 2026-02-04 Tianyi Gong , Zijian Cao , Zixing Zhang , Jiangkai Wu , Xinggong Zhang , Shuguang Cui , Fangxin Wang

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…

计算机视觉与模式识别 · 计算机科学 2024-05-28 Wenqi Ouyang , Yi Dong , Lei Yang , Jianlou Si , Xingang Pan
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