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Related papers: Shape-aware Text-driven Layered Video Editing

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Scene text segmentation aims at cropping texts from scene images, which is usually used to help generative models edit or remove texts. The existing text segmentation methods tend to involve various text-related supervisions for better…

Computer Vision and Pattern Recognition · Computer Science 2024-07-25 Haiyang Yu , Teng Fu , Bin Li , Xiangyang Xue

Most real-world image editing tasks require multiple sequential edits to achieve desired results. Current editing approaches, primarily designed for single-object modifications, struggle with sequential editing: especially with maintaining…

Computer Vision and Pattern Recognition · Computer Science 2025-05-05 Daneul Kim , Jaeah Lee , Jaesik Park

Video colorization is a challenging task that involves inferring plausible and temporally consistent colors for grayscale frames. In this paper, we present ColorDiffuser, an adaptation of a pre-trained text-to-image latent diffusion model…

Computer Vision and Pattern Recognition · Computer Science 2023-06-05 Hanyuan Liu , Minshan Xie , Jinbo Xing , Chengze Li , Tien-Tsin Wong

Diffusion models have recently advanced video editing, yet controllable editing remains challenging due to the need for precise manipulation of diverse object properties. Current methods require different control signal for diverse editing…

Computer Vision and Pattern Recognition · Computer Science 2025-09-03 Yuqing Chen , Junjie Wang , Lin Liu , Ruihang Chu , Xiaopeng Zhang , Qi Tian , Yujiu Yang

With the rapid development of generative technology, current generative models can generate high-fidelity digital content and edit it in a controlled manner. However, there is a risk that malicious individuals might misuse these…

Computer Vision and Pattern Recognition · Computer Science 2025-08-06 Junjie Cao , Kaizhou Li , Xinchun Yu , Hongxiang Li , Xiaoping Zhang

Drag-based editing allows precise object manipulation through point-based control, offering user convenience. However, current methods often suffer from a geometric inconsistency problem by focusing exclusively on matching user-defined…

Graphics · Computer Science 2025-07-14 Gwanhyeong Koo , Sunjae Yoon , Younghwan Lee , Ji Woo Hong , Chang D. Yoo

We describe a method to extract persistent elements of a dynamic scene from an input video. We represent each scene element as a \emph{Deformable Sprite} consisting of three components: 1) a 2D texture image for the entire video, 2)…

Computer Vision and Pattern Recognition · Computer Science 2022-04-15 Vickie Ye , Zhengqi Li , Richard Tucker , Angjoo Kanazawa , Noah Snavely

While image editing has advanced rapidly, video editing remains less explored, facing challenges in consistency, control, and generalization. We study the design space of data, architecture, and control, and introduce \emph{EasyV2V}, a…

Computer Vision and Pattern Recognition · Computer Science 2025-12-19 Jinjie Mai , Chaoyang Wang , Guocheng Gordon Qian , Willi Menapace , Sergey Tulyakov , Bernard Ghanem , Peter Wonka , Ashkan Mirzaei

The exponential growth of short-video content has ignited a surge in the necessity for efficient, automated solutions to video editing, with challenges arising from the need to understand videos and tailor the editing according to user…

Computer Vision and Pattern Recognition · Computer Science 2025-01-13 Dabing Cheng , Haosen Zhan , Xingchen Zhao , Guisheng Liu , Zemin Li , Jinghui Xie , Zhao Song , Weiguo Feng , Bingyue Peng

Text-guided diffusion models have shown superior performance in image/video generation and editing. While few explorations have been performed in 3D scenarios. In this paper, we discuss three fundamental and interesting problems on this…

Computer Vision and Pattern Recognition · Computer Science 2023-10-13 Gang Li , Heliang Zheng , Chaoyue Wang , Chang Li , Changwen Zheng , Dacheng Tao

Text-to-video generation aims to produce a video based on a given prompt. Recently, several commercial video models have been able to generate plausible videos with minimal noise, excellent details, and high aesthetic scores. However, these…

Computer Vision and Pattern Recognition · Computer Science 2024-01-18 Haoxin Chen , Yong Zhang , Xiaodong Cun , Menghan Xia , Xintao Wang , Chao Weng , Ying Shan

Most model-free visual object tracking methods formulate the tracking task as object location estimation given by a 2D segmentation or a bounding box in each video frame. We argue that this representation is limited and instead propose to…

Computer Vision and Pattern Recognition · Computer Science 2023-04-14 Denys Rozumnyi , Jiri Matas , Marc Pollefeys , Vittorio Ferrari , Martin R. Oswald

Text-based video editing has recently attracted considerable interest in changing the style or replacing the objects with a similar structure. Beyond this, we demonstrate that properties such as shape, size, location, motion, etc., can also…

Computer Vision and Pattern Recognition · Computer Science 2024-11-19 Yue Ma , Xiaodong Cun , Sen Liang , Jinbo Xing , Yingqing He , Chenyang Qi , Siran Chen , Qifeng Chen

Image-to-video adaptation seeks to efficiently adapt image models for use in the video domain. Instead of finetuning the entire image backbone, many image-to-video adaptation paradigms use lightweight adapters for temporal modeling on top…

Computer Vision and Pattern Recognition · Computer Science 2024-07-10 Rui Qian , Shuangrui Ding , Dahua Lin

While 2D diffusion models have achieved remarkable success in identity-preserving personalization, extending this capability to 3D assets remains a significant challenge due to the complexities of multi-view consistency and spatial control.…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Jinxin Ai , Matthias Nießner , Ziya Erkoç

We propose Latent-Shift -- an efficient text-to-video generation method based on a pretrained text-to-image generation model that consists of an autoencoder and a U-Net diffusion model. Learning a video diffusion model in the latent space…

Computer Vision and Pattern Recognition · Computer Science 2023-04-19 Jie An , Songyang Zhang , Harry Yang , Sonal Gupta , Jia-Bin Huang , Jiebo Luo , Xi Yin

Text-guided 3D editing aims to precisely edit semantically relevant local 3D regions, which has significant potential for various practical applications ranging from 3D games to film production. Existing methods typically follow a…

Graphics · Computer Science 2025-06-04 Yang Zheng , Mengqi Huang , Nan Chen , Zhendong Mao

This paper presents a novel approach for text/speech-driven animation of a photo-realistic head model based on blend-shape geometry, dynamic textures, and neural rendering. Training a VAE for geometry and texture yields a parametric model…

Computer Vision and Pattern Recognition · Computer Science 2023-09-06 Wolfgang Paier , Anna Hilsmann , Peter Eisert

We propose a novel feed-forward 3D editing framework called Shap-Editor. Prior research on editing 3D objects primarily concentrated on editing individual objects by leveraging off-the-shelf 2D image editing networks. This is achieved via a…

Computer Vision and Pattern Recognition · Computer Science 2023-12-15 Minghao Chen , Junyu Xie , Iro Laina , Andrea Vedaldi

Diffusion-based point editing methods have gained significant traction in image editing tasks due to their ability to manipulate image semantics and fine details by applying localized perturbations on the manifold of noise latent. However,…

Computer Vision and Pattern Recognition · Computer Science 2026-05-14 Haoyang Hu , Masataka Seo , Yen-Wei Chen