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This paper proposes Instruct 4D-to-4D that achieves 4D awareness and spatial-temporal consistency for 2D diffusion models to generate high-quality instruction-guided dynamic scene editing results. Traditional applications of 2D diffusion…

Computer Vision and Pattern Recognition · Computer Science 2024-06-14 Linzhan Mou , Jun-Kun Chen , Yu-Xiong Wang

Diffusion models have shown great results in image generation and in image editing. However, current approaches are limited to low resolutions due to the computational cost of training diffusion models for high-resolution generation. We…

Computer Vision and Pattern Recognition · Computer Science 2022-10-25 Johannes Ackermann , Minjun Li

Despite the success in large-scale text-to-image generation and text-conditioned image editing, existing methods still struggle to produce consistent generation and editing results. For example, generation approaches usually fail to…

Computer Vision and Pattern Recognition · Computer Science 2023-04-18 Mingdeng Cao , Xintao Wang , Zhongang Qi , Ying Shan , Xiaohu Qie , Yinqiang Zheng

Generating 3D scenes from human motion sequences supports numerous applications, including virtual reality and architectural design. However, previous auto-regression-based human-aware 3D scene generation methods have struggled to…

Computer Vision and Pattern Recognition · Computer Science 2024-08-21 Xiaolin Hong , Hongwei Yi , Fazhi He , Qiong Cao

Recent advances in video diffusion models have enabled the generation of high-quality videos. However, these videos still suffer from unrealistic deformations, semantic violations, and physical inconsistencies that are largely rooted in the…

Computer Vision and Pattern Recognition · Computer Science 2025-11-04 Shurui Gui , Deep Anil Patel , Xiner Li , Martin Renqiang Min

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

The use of denoising diffusion models is becoming increasingly popular in the field of image editing. However, current approaches often rely on either image-guided methods, which provide a visual reference but lack control over semantic…

Computer Vision and Pattern Recognition · Computer Science 2025-01-07 Zhanbo Feng , Zenan Ling , Xinyu Lu , Ci Gong , Feng Zhou , Wugedele Bao , Jie Li , Fan Yang , Robert C. Qiu

We present ShapeShift, a method for arranging rigid objects into configurations that visually convey semantic concepts specified by natural language. While pretrained diffusion models provide powerful semantic guidance, such as Score…

Computer Vision and Pattern Recognition · Computer Science 2026-02-24 Vihaan Misra , Peter Schaldenbrand , Jean Oh

In this work, we introduce Wonder3D, a novel method for efficiently generating high-fidelity textured meshes from single-view images.Recent methods based on Score Distillation Sampling (SDS) have shown the potential to recover 3D geometry…

Computer Vision and Pattern Recognition · Computer Science 2023-11-10 Xiaoxiao Long , Yuan-Chen Guo , Cheng Lin , Yuan Liu , Zhiyang Dou , Lingjie Liu , Yuexin Ma , Song-Hai Zhang , Marc Habermann , Christian Theobalt , Wenping Wang

This paper proposes ProEdit - a simple yet effective framework for high-quality 3D scene editing guided by diffusion distillation in a novel progressive manner. Inspired by the crucial observation that multi-view inconsistency in scene…

Computer Vision and Pattern Recognition · Computer Science 2024-11-08 Jun-Kun Chen , Yu-Xiong Wang

Despite remarkable achievements in video synthesis, achieving granular control over complex dynamics, such as nuanced movement among multiple interacting objects, still presents a significant hurdle for dynamic world modeling, compounded by…

Computer Vision and Pattern Recognition · Computer Science 2024-03-21 Pengxiang Li , Kai Chen , Zhili Liu , Ruiyuan Gao , Lanqing Hong , Guo Zhou , Hua Yao , Dit-Yan Yeung , Huchuan Lu , Xu Jia

In layout-to-image (L2I) synthesis, controlled complex scenes are generated from coarse information like bounding boxes. Such a task is exciting to many downstream applications because the input layouts offer strong guidance to the…

Computer Vision and Pattern Recognition · Computer Science 2025-03-18 Ruyu Wang , Xuefeng Hou , Sabrina Schmedding , Marco F. Huber

Research in vision-language models has seen rapid developments off-late, enabling natural language-based interfaces for image generation and manipulation. Many existing text guided manipulation techniques are restricted to specific classes…

Computer Vision and Pattern Recognition · Computer Science 2024-05-07 Paramanand Chandramouli , Kanchana Vaishnavi Gandikota

In this paper, we present DesignDiffusion, a simple yet effective framework for the novel task of synthesizing design images from textual descriptions. A primary challenge lies in generating accurate and style-consistent textual and visual…

Computer Vision and Pattern Recognition · Computer Science 2025-03-04 Zhendong Wang , Jianmin Bao , Shuyang Gu , Dong Chen , Wengang Zhou , Houqiang Li

Generating realistic 3D scenes is an area of growing interest in computer vision and robotics. However, creating high-quality, diverse synthetic 3D content often requires expert intervention, making it costly and complex. Recently, efforts…

Computer Vision and Pattern Recognition · Computer Science 2024-12-11 Siyi Hu , Diego Martin Arroyo , Stephanie Debats , Fabian Manhardt , Luca Carlone , Federico Tombari

Video Diffusion Models have been developed for video generation, usually integrating text and image conditioning to enhance control over the generated content. Despite the progress, ensuring consistency across frames remains a challenge,…

Computer Vision and Pattern Recognition · Computer Science 2024-11-12 Tian Xia , Xuweiyi Chen , Sihan Xu

Addressing the limitations of text as a source of accurate layout representation in text-conditional diffusion models, many works incorporate additional signals to condition certain attributes within a generated image. Although successful,…

Computer Vision and Pattern Recognition · Computer Science 2024-01-18 Jonghyun Lee , Hansam Cho , Youngjoon Yoo , Seoung Bum Kim , Yonghyun Jeong

Consistent human-centric image and video synthesis aims to generate images or videos with new poses while preserving appearance consistency with a given reference image, which is crucial for low-cost visual content creation. Recent advances…

Computer Vision and Pattern Recognition · Computer Science 2024-12-20 Mingdeng Cao , Chong Mou , Ziyang Yuan , Xintao Wang , Zhaoyang Zhang , Ying Shan , Yinqiang Zheng

Text-to-image diffusion models have shown great potential for image editing, with techniques such as text-based and object-dragging methods emerging as key approaches. However, each of these methods has inherent limitations: text-based…

Computer Vision and Pattern Recognition · Computer Science 2025-10-10 Haoran Yu , Yi Shi

Generative diffusion models have advanced image editing with high-quality results and intuitive interfaces such as prompts and semantic drawing. However, these interfaces lack precise control, and the associated methods typically specialize…

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