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This paper proposes ConsistDreamer - a novel framework that lifts 2D diffusion models with 3D awareness and 3D consistency, thus enabling high-fidelity instruction-guided scene editing. To overcome the fundamental limitation of missing 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-06-14 Jun-Kun Chen , Samuel Rota Bulò , Norman Müller , Lorenzo Porzi , Peter Kontschieder , Yu-Xiong Wang

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

We introduce VIVE3D, a novel approach that extends the capabilities of image-based 3D GANs to video editing and is able to represent the input video in an identity-preserving and temporally consistent way. We propose two new building…

Computer Vision and Pattern Recognition · Computer Science 2023-03-29 Anna Frühstück , Nikolaos Sarafianos , Yuanlu Xu , Peter Wonka , Tony Tung

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

Text-driven 3D editing seeks to modify 3D scenes according to textual descriptions, and most existing approaches tackle this by adapting pre-trained 2D image editors to multi-view inputs. However, without explicit control over multi-view…

Computer Vision and Pattern Recognition · Computer Science 2026-02-20 Zhe Zhu , Honghua Chen , Peng Li , Mingqiang Wei

Recent advances in diffusion models have enabled high-quality generation and manipulation of images guided by texts, as well as concept learning from images. However, naive applications of existing methods to editing tasks that require…

Computer Vision and Pattern Recognition · Computer Science 2025-12-29 Xudong Liu , Zikun Chen , Ruowei Jiang , Ziyi Wu , Kejia Yin , Han Zhao , Parham Aarabi , Igor Gilitschenski

Video depth estimation is essential for providing 3D scene structure in applications ranging from autonomous driving to mixed reality. Current end-to-end video depth models have established state-of-the-art performance. Although current…

Computer Vision and Pattern Recognition · Computer Science 2026-04-22 Daewon Yoon , Injun Baek , Sangyu Han , Yearim Kim , Nojun Kwak

While generative video models have achieved remarkable fidelity and consistency, applying these capabilities to video editing remains a complex challenge. Recent research has explored motion controllability as a means to enhance…

Computer Vision and Pattern Recognition · Computer Science 2025-11-26 Ryan Burgert , Charles Herrmann , Forrester Cole , Michael S Ryoo , Neal Wadhwa , Andrey Voynov , Nataniel Ruiz

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

We present a novel framework for mesh reconstruction from unstructured point clouds by taking advantage of the learned visibility of the 3D points in the virtual views and traditional graph-cut based mesh generation. Specifically, we first…

Computer Vision and Pattern Recognition · Computer Science 2021-08-20 Shuang Song , Zhaopeng Cui , Rongjun Qin

Instruction-guided generative models, especially those using text-to-image (T2I) and text-to-video (T2V) diffusion frameworks, have advanced the field of content editing in recent years. To extend these capabilities to 4D scene, we…

Computer Vision and Pattern Recognition · Computer Science 2025-04-02 Hasan Iqbal , Nazmul Karim , Umar Khalid , Azib Farooq , Zichun Zhong , Chen Chen , Jing Hua

Drag-based editing has become popular in 2D content creation, driven by the capabilities of image generative models. However, extending this technique to 3D remains a challenge. Existing 3D drag-based editing methods, whether employing…

Computer Vision and Pattern Recognition · Computer Science 2024-10-22 Honghua Chen , Yushi Lan , Yongwei Chen , Yifan Zhou , Xingang Pan

Face attribute editing plays a pivotal role in various applications. However, existing methods encounter challenges in achieving high-quality results while preserving identity, editing faithfulness, and temporal consistency. These…

Computer Vision and Pattern Recognition · Computer Science 2024-04-15 Guangzhi Wang , Tianyi Chen , Kamran Ghasedi , HsiangTao Wu , Tianyu Ding , Chris Nuesmeyer , Ilya Zharkov , Mohan Kankanhalli , Luming Liang

With the help of Score Distillation Sampling (SDS) and the rapid development of neural 3D representations, some methods have been proposed to perform 3D editing such as adding additional geometries, or overwriting textures. However,…

Computer Vision and Pattern Recognition · Computer Science 2024-07-10 Yige Chen , Teng Hu , Yizhe Tang , Siyuan Chen , Ang Chen , Ran Yi

In this report, we present MagicEdit, a surprisingly simple yet effective solution to the text-guided video editing task. We found that high-fidelity and temporally coherent video-to-video translation can be achieved by explicitly…

Computer Vision and Pattern Recognition · Computer Science 2023-08-29 Jun Hao Liew , Hanshu Yan , Jianfeng Zhang , Zhongcong Xu , Jiashi Feng

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

We consider the problem of editing 3D objects and scenes based on open-ended language instructions. A common approach to this problem is to use a 2D image generator or editor to guide the 3D editing process, obviating the need for 3D data.…

Computer Vision and Pattern Recognition · Computer Science 2024-12-02 Minghao Chen , Iro Laina , Andrea Vedaldi

This paper explores the innovative application of Stable Video Diffusion (SVD), a diffusion model that revolutionizes the creation of dynamic video content from static images. As digital media and design industries accelerate, SVD emerges…

Human-Computer Interaction · Computer Science 2024-05-24 Elijah Miller , Thomas Dupont , Mingming Wang

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

Controlling illumination during video post-production is a crucial yet elusive goal in computational photography. Existing methods often lack flexibility, restricting users to certain relighting models. This paper introduces ReLumix, a…

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