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Controllable scene synthesis consists of generating 3D information that satisfy underlying specifications. Thereby, these specifications should be abstract, i.e. allowing easy user interaction, whilst providing enough interface for detailed…

Computer Vision and Pattern Recognition · Computer Science 2021-08-20 Helisa Dhamo , Fabian Manhardt , Nassir Navab , Federico Tombari

Surgical simulation plays a pivotal role in training novice surgeons, accelerating their learning curve and reducing intra-operative errors. However, conventional simulation tools fall short in providing the necessary photorealism and the…

Computer Vision and Pattern Recognition · Computer Science 2025-06-16 Ssharvien Kumar Sivakumar , Yannik Frisch , Ghazal Ghazaei , Anirban Mukhopadhyay

State-of-the-art diffusion models can generate highly realistic images based on various conditioning like text, segmentation, and depth. However, an essential aspect often overlooked is the specific camera geometry used during image…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Andrey Voynov , Amir Hertz , Moab Arar , Shlomi Fruchter , Daniel Cohen-Or

Centred on content modification and style preservation, Scene Text Editing (STE) remains a challenging task despite considerable progress in text-to-image synthesis and text-driven image manipulation recently. GAN-based STE methods…

Computer Vision and Pattern Recognition · Computer Science 2024-10-15 Weichao Zeng , Yan Shu , Zhenhang Li , Dongbao Yang , Yu Zhou

Despite the recent progress in text-to-video generation, existing studies usually overlook the issue that only spatial contents but not temporal motions in synthesized videos are under the control of text. Towards such a challenge, this…

Computer Vision and Pattern Recognition · Computer Science 2023-12-06 Xi Chen , Zhiheng Liu , Mengting Chen , Yutong Feng , Yu Liu , Yujun Shen , Hengshuang Zhao

Text-guided diffusion models have greatly advanced image editing and generation. However, achieving physically consistent image retouching with precise parameter control (e.g., exposure, white balance, zoom) remains challenging. Existing…

Computer Vision and Pattern Recognition · Computer Science 2025-11-27 Qirui Yang , Yang Yang , Ying Zeng , Xiaobin Hu , Bo Li , Huanjing Yue , Jingyu Yang , Peng-Tao Jiang

Accurate reconstruction of complex dynamic scenes from just a single viewpoint continues to be a challenging task in computer vision. Current dynamic novel view synthesis methods typically require videos from many different camera…

Computer Vision and Pattern Recognition · Computer Science 2024-07-08 Basile Van Hoorick , Rundi Wu , Ege Ozguroglu , Kyle Sargent , Ruoshi Liu , Pavel Tokmakov , Achal Dave , Changxi Zheng , Carl Vondrick

Previous works have explored various customized generation tasks given a reference image, but they still face limitations in generating consistent fine-grained details. In this paper, our aim is to solve the inconsistency problem of…

Computer Vision and Pattern Recognition · Computer Science 2025-11-26 Ziheng Ouyang , Yiren Song , Yaoli Liu , Shihao Zhu , Qibin Hou , Ming-Ming Cheng , Mike Zheng Shou

We focus on the foundational task of Scene Staging: given a reference scene image and a text condition specifying an actor category to be generated in the scene and its spatial relation to the scene, the goal is to synthesize an output…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Cong Xie , Che Wang , Yan Zhang , Ruiqi Yu , Han Zou , Zheng Pan , Zhenpeng Zhan

Realistic shadow generation is a critical component for high-quality image compositing and visual effects, yet existing methods suffer from certain limitations: Physics-based approaches require a 3D scene geometry, which is often…

Computer Vision and Pattern Recognition · Computer Science 2024-12-17 Onur Tasar , Clément Chadebec , Benjamin Aubin

Existing techniques for dynamic scene reconstruction from multiple wide-baseline cameras primarily focus on reconstruction in controlled environments, with fixed calibrated cameras and strong prior constraints. This paper introduces a…

Computer Vision and Pattern Recognition · Computer Science 2020-08-04 Armin Mustafa , Marco Volino , Hansung Kim , Jean-Yves Guillemaut , Adrian Hilton

We propose MotionAgent, enabling fine-grained motion control for text-guided image-to-video generation. The key technique is the motion field agent that converts motion information in text prompts into explicit motion fields, providing…

Computer Vision and Pattern Recognition · Computer Science 2025-10-16 Xinyao Liao , Xianfang Zeng , Liao Wang , Gang Yu , Guosheng Lin , Chi Zhang

Following the advancements in text-guided image generation technology exemplified by Stable Diffusion, video generation is gaining increased attention in the academic community. However, relying solely on text guidance for video generation…

Computer Vision and Pattern Recognition · Computer Science 2024-09-17 Cong Wang , Jiaxi Gu , Panwen Hu , Haoyu Zhao , Yuanfan Guo , Jianhua Han , Hang Xu , Xiaodan Liang

Material reconstruction from a photograph is a key component of 3D content creation democratization. We propose to formulate this ill-posed problem as a controlled synthesis one, leveraging the recent progress in generative deep networks.…

Computer Vision and Pattern Recognition · Computer Science 2024-08-28 Giuseppe Vecchio , Rosalie Martin , Arthur Roullier , Adrien Kaiser , Romain Rouffet , Valentin Deschaintre , Tamy Boubekeur

High-quality driving video generation is crucial for providing training data for autonomous driving models. However, current generative models rarely focus on enhancing camera motion control under multi-view tasks, which is essential for…

Computer Vision and Pattern Recognition · Computer Science 2024-09-12 Yining Yao , Xi Guo , Chenjing Ding , Wei Wu

Recent years have witnessed some exciting developments in the domain of generating images from scene-based text descriptions. These approaches have primarily focused on generating images from a static text description and are limited to…

Computer Vision and Pattern Recognition · Computer Science 2019-05-10 Gaurav Mittal , Shubham Agrawal , Anuva Agarwal , Sushant Mehta , Tanya Marwah

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

Recent advances in illumination control extend image-based methods to video, yet still facing a trade-off between lighting fidelity and temporal consistency. Moving beyond relighting, a key step toward generative modeling of real-world…

Computer Vision and Pattern Recognition · Computer Science 2025-12-16 Tianqi Liu , Zhaoxi Chen , Zihao Huang , Shaocong Xu , Saining Zhang , Chongjie Ye , Bohan Li , Zhiguo Cao , Wei Li , Hao Zhao , Ziwei Liu

Recent text-to-image models have revolutionized image generation, but they still struggle with maintaining concept consistency across generated images. While existing works focus on character consistency, they often overlook the crucial…

Computer Vision and Pattern Recognition · Computer Science 2025-10-28 Quanjian Song , Donghao Zhou , Jingyu Lin , Fei Shen , Jiaze Wang , Xiaowei Hu , Cunjian Chen , Pheng-Ann Heng

Recent advances in diffusion models bring new vitality to visual content creation. However, current text-to-video generation models still face significant challenges such as high training costs, substantial data requirements, and…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Sicong Feng , Jielong Yang , Li Peng