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Related papers: Language-Guided Joint Audio-Visual Editing via One…

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Text-to-image diffusion models have demonstrated remarkable progress in synthesizing high-quality images from text prompts, which boosts researches on prompt-based image editing that edits a source image according to a target prompt.…

Computer Vision and Pattern Recognition · Computer Science 2024-11-19 Kejie Wang , Xuemeng Song , Meng Liu , Jin Yuan , Weili Guan

When watching videos, the occurrence of a visual event is often accompanied by an audio event, e.g., the voice of lip motion, the music of playing instruments. There is an underlying correlation between audio and visual events, which can be…

Multimedia · Computer Science 2020-08-19 Ying Cheng , Ruize Wang , Zhihao Pan , Rui Feng , Yuejie Zhang

Editing videos with textual guidance has garnered popularity due to its streamlined process which mandates users to solely edit the text prompt corresponding to the source video. Recent studies have explored and exploited large-scale…

Computer Vision and Pattern Recognition · Computer Science 2024-12-17 Yuanzhi Wang , Yong Li , Mengyi Liu , Xiaoya Zhang , Xin Liu , Zhen Cui , Antoni B. Chan

Recent advances in text-guided image editing enable users to perform image edits through simple text inputs, leveraging the extensive priors of multi-step diffusion-based text-to-image models. However, these methods often fall short of the…

Computer Vision and Pattern Recognition · Computer Science 2025-06-03 Trong-Tung Nguyen , Quang Nguyen , Khoi Nguyen , Anh Tran , Cuong Pham

Recent diffusion-based image editing approaches have exhibited impressive editing capabilities in images with simple compositions. However, localized editing in complex scenarios has not been well-studied in the literature, despite its…

Computer Vision and Pattern Recognition · Computer Science 2023-12-22 Qi Mao , Lan Chen , Yuchao Gu , Zhen Fang , Mike Zheng Shou

Diffusion models have achieved significant success in image and video generation. This motivates a growing interest in video editing tasks, where videos are edited according to provided text descriptions. However, most existing approaches…

Computer Vision and Pattern Recognition · Computer Science 2023-12-01 Zhen Xing , Qi Dai , Zihao Zhang , Hui Zhang , Han Hu , Zuxuan Wu , Yu-Gang Jiang

The generation of sounding videos has seen significant advancements with the advent of diffusion models. However, existing methods often lack the fine-grained control needed to generate viewpoint-specific content from larger, immersive…

Audio-driven one-shot talking face generation methods are usually trained on video resources of various persons. However, their created videos often suffer unnatural mouth shapes and asynchronous lips because those methods struggle to learn…

Computer Vision and Pattern Recognition · Computer Science 2021-12-07 Suzhen Wang , Lincheng Li , Yu Ding , Xin Yu

Reconstructing 3D scenes and synthesizing novel views from sparse input views is a highly challenging task. Recent advances in video diffusion models have demonstrated strong temporal reasoning capabilities, making them a promising tool for…

Computer Vision and Pattern Recognition · Computer Science 2025-11-18 Yuqi Zhang , Guanying Chen , Jiaxing Chen , Chuanyu Fu , Chuan Huang , Shuguang Cui

Recent advancements in 3D editing have highlighted the potential of text-driven methods in real-time, user-friendly AR/VR applications. However, current methods rely on 2D diffusion models without adequately considering multi-view…

Computer Vision and Pattern Recognition · Computer Science 2025-04-21 Dong In Lee , Hyeongcheol Park , Jiyoung Seo , Eunbyung Park , Hyunje Park , Ha Dam Baek , Sangheon Shin , Sangmin Kim , Sangpil Kim

Existing diffusion-based methods have achieved impressive results in human motion editing. However, these methods often exhibit significant ghosting and body distortion in unseen in-the-wild cases. In this paper, we introduce…

Computer Vision and Pattern Recognition · Computer Science 2024-10-16 Yi Zuo , Lingling Li , Licheng Jiao , Fang Liu , Xu Liu , Wenping Ma , Shuyuan Yang , Yuwei Guo

Recent developments in the field of diffusion models have demonstrated an exceptional capacity to generate high-quality prompt-conditioned image edits. Nevertheless, previous approaches have primarily relied on textual prompts for image…

Computer Vision and Pattern Recognition · Computer Science 2024-08-07 Goirik Chakrabarty , Aditya Chandrasekar , Ramya Hebbalaguppe , Prathosh AP

Generative image editing has recently witnessed extremely fast-paced growth. Some works use high-level conditioning such as text, while others use low-level conditioning. Nevertheless, most of them lack fine-grained control over the…

Computer Vision and Pattern Recognition · Computer Science 2024-04-10 Vidit Goel , Elia Peruzzo , Yifan Jiang , Dejia Xu , Xingqian Xu , Nicu Sebe , Trevor Darrell , Zhangyang Wang , Humphrey Shi

The objective of this work is to extract target speaker's voice from a mixture of voices using visual cues. Existing works on audio-visual speech separation have demonstrated their performance with promising intelligibility, but maintaining…

Audio and Speech Processing · Electrical Eng. & Systems 2023-10-31 Suyeon Lee , Chaeyoung Jung , Youngjoon Jang , Jaehun Kim , Joon Son Chung

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

Instruction-based video editing aims to modify an input video according to a natural-language instruction while preserving content fidelity and temporal coherence. However, existing diffusion-based approaches are often trained on paired…

Computer Vision and Pattern Recognition · Computer Science 2025-12-19 Xiaoyan Cong , Haotian Yang , Angtian Wang , Yizhi Wang , Yiding Yang , Canyu Zhang , Chongyang Ma

The generative AI revolution has recently expanded to videos. Nevertheless, current state-of-the-art video models are still lagging behind image models in terms of visual quality and user control over the generated content. In this work, we…

Computer Vision and Pattern Recognition · Computer Science 2023-11-21 Michal Geyer , Omer Bar-Tal , Shai Bagon , Tali Dekel

Visual prompt, a pair of before-and-after edited images, can convey indescribable imagery transformations and prosper in image editing. However, current visual prompt methods rely on a pretrained text-guided image-to-image generative model…

Computer Vision and Pattern Recognition · Computer Science 2025-01-28 Pengcheng Xu , Qingnan Fan , Fei Kou , Shuai Qin , Hong Gu , Ruoyu Zhao , Charles Ling , Boyu Wang

Existing text-to-image editing methods tend to excel either in rigid or non-rigid editing but encounter challenges when combining both, resulting in misaligned outputs with the provided text prompts. In addition, integrating reference…

Computer Vision and Pattern Recognition · Computer Science 2024-01-05 Jiacheng Wang , Ping Liu , Wei Xu

We propose a self-supervised approach for learning to perform audio source separation in videos based on natural language queries, using only unlabeled video and audio pairs as training data. A key challenge in this task is learning to…

Computer Vision and Pattern Recognition · Computer Science 2023-09-26 Reuben Tan , Arijit Ray , Andrea Burns , Bryan A. Plummer , Justin Salamon , Oriol Nieto , Bryan Russell , Kate Saenko
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