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Related papers: CameraCtrl: Enabling Camera Control for Text-to-Vi…

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Camera and human motion controls have been extensively studied for video generation, but existing approaches typically address them separately, suffering from limited data with high-quality annotations for both aspects. To overcome this, we…

Computer Vision and Pattern Recognition · Computer Science 2025-09-23 Chenjie Cao , Jingkai Zhou , Shikai Li , Jingyun Liang , Chaohui Yu , Fan Wang , Xiangyang Xue , Yanwei Fu

We introduce MVControl, a novel neural network architecture that enhances existing pre-trained multi-view 2D diffusion models by incorporating additional input conditions, e.g. edge maps. Our approach enables the generation of controllable…

Computer Vision and Pattern Recognition · Computer Science 2023-11-29 Zhiqi Li , Yiming Chen , Lingzhe Zhao , Peidong Liu

In the last two years, text-to-image diffusion models have become extremely popular. As their quality and usage increase, a major concern has been the need for better output control. In addition to prompt engineering, one effective method…

Computer Vision and Pattern Recognition · Computer Science 2024-11-25 Clément Bonnet , Ariel N. Lee , Franck Wertel , Antoine Tamano , Tanguy Cizain , Pablo Ducru

Controlling the movements of dynamic objects and the camera within generated videos is a meaningful yet challenging task. Due to the lack of datasets with comprehensive 6D pose annotations, existing text-to-video methods can not…

Computer Vision and Pattern Recognition · Computer Science 2025-07-22 Xincheng Shuai , Henghui Ding , Zhenyuan Qin , Hao Luo , Xingjun Ma , Dacheng Tao

Recent advancements in video generation have been remarkable, yet many existing methods struggle with issues of consistency and poor text-video alignment. Moreover, the field lacks effective techniques for text-guided video inpainting, a…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Bojia Zi , Shihao Zhao , Xianbiao Qi , Jianan Wang , Yukai Shi , Qianyu Chen , Bin Liang , Kam-Fai Wong , Lei Zhang

This study aims to achieve more precise and versatile object control in image-to-video (I2V) generation. Current methods typically represent the spatial movement of target objects with 2D trajectories, which often fail to capture user…

Computer Vision and Pattern Recognition · Computer Science 2025-06-25 Zhouxia Wang , Yushi Lan , Shangchen Zhou , Chen Change Loy

In recent years there have been remarkable breakthroughs in image-to-video generation. However, the 3D consistency and camera controllability of generated frames have remained unsolved. Recent studies have attempted to incorporate camera…

Computer Vision and Pattern Recognition · Computer Science 2024-10-15 Dejia Xu , Yifan Jiang , Chen Huang , Liangchen Song , Thorsten Gernoth , Liangliang Cao , Zhangyang Wang , Hao Tang

Diffusion models emerged as a leading approach in text-to-image generation, producing high-quality images from textual descriptions. However, attempting to achieve detailed control to get a desired image solely through text remains a…

Computer Vision and Pattern Recognition · Computer Science 2026-02-12 Pablo Domingo-Gregorio , Javier Ruiz-Hidalgo

Character Animation aims to generating character videos from still images through driving signals. Currently, diffusion models have become the mainstream in visual generation research, owing to their robust generative capabilities. However,…

Computer Vision and Pattern Recognition · Computer Science 2024-06-14 Li Hu , Xin Gao , Peng Zhang , Ke Sun , Bang Zhang , Liefeng Bo

Recent advancements in personalized Text-to-Video (T2V) generation have made significant strides in synthesizing character-specific content. However, these methods face a critical limitation: the inability to perform fine-grained control…

Computer Vision and Pattern Recognition · Computer Science 2026-01-06 Haopeng Fang , Di Qiu , Binjie Mao , He Tang

State-of-the-art image captioners can generate accurate sentences to describe images in a sequence to sequence manner without considering the controllability and interpretability. This, however, is far from making image captioning widely…

Computer Vision and Pattern Recognition · Computer Science 2022-05-26 Luka Maxwell

Recent advances in text-to-image generation with diffusion models present transformative capabilities in image quality. However, user controllability of the generated image, and fast adaptation to new tasks still remains an open challenge,…

Computer Vision and Pattern Recognition · Computer Science 2023-02-17 Omer Bar-Tal , Lior Yariv , Yaron Lipman , Tali Dekel

Recent text-to-image diffusion models are able to generate convincing results of unprecedented quality. However, it is nearly impossible to control the shapes of different regions/objects or their layout in a fine-grained fashion. Previous…

Computer Vision and Pattern Recognition · Computer Science 2023-09-06 Omri Avrahami , Thomas Hayes , Oran Gafni , Sonal Gupta , Yaniv Taigman , Devi Parikh , Dani Lischinski , Ohad Fried , Xi Yin

World models based on video generation demonstrate remarkable potential for simulating interactive environments but face persistent difficulties in two key areas: maintaining long-term content consistency when scenes are revisited and…

Computer Vision and Pattern Recognition · Computer Science 2026-02-27 Tianxing Xu , Zixuan Wang , Guangyuan Wang , Li Hu , Zhongyi Zhang , Peng Zhang , Bang Zhang , Song-Hai Zhang

To enhance the controllability of text-to-image diffusion models, current ControlNet-like models have explored various control signals to dictate image attributes. However, existing methods either handle conditions inefficiently or use a…

Computer Vision and Pattern Recognition · Computer Science 2025-09-29 Qingdong He , Jinlong Peng , Pengcheng Xu , Boyuan Jiang , Xiaobin Hu , Donghao Luo , Yong Liu , Yabiao Wang , Chengjie Wang , Xiangtai Li , Jiangning Zhang

Diffusion models have recently become the dominant paradigm for image generation, yet existing systems struggle to interpret and follow numeric instructions for adjusting semantic attributes. In real-world creative scenarios, especially…

Computer Vision and Pattern Recognition · Computer Science 2026-01-12 Die Chen , Zhongjie Duan , Zhiwen Li , Cen Chen , Daoyuan Chen , Yaliang Li , Yingda Chen

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

Text-guided color editing in images and videos is a fundamental yet unsolved problem, requiring fine-grained manipulation of color attributes, including albedo, light source color, and ambient lighting, while preserving physical consistency…

Generative models have advanced significantly in realistic image synthesis, with diffusion models excelling in quality and stability. Recent multi-view diffusion models improve 3D-aware street view generation, but they struggle to produce…

Computer Vision and Pattern Recognition · Computer Science 2026-02-13 Ji Li , Zhiwei Li , Shihao Li , Zhenjiang Yu , Boyang Wang , Haiou Liu

This paper presents a method that allows users to design cinematic video shots in the context of image-to-video generation. Shot design, a critical aspect of filmmaking, involves meticulously planning both camera movements and object…

Computer Vision and Pattern Recognition · Computer Science 2025-02-07 Jinbo Xing , Long Mai , Cusuh Ham , Jiahui Huang , Aniruddha Mahapatra , Chi-Wing Fu , Tien-Tsin Wong , Feng Liu