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Recently, text-to-image generation models have achieved remarkable advancements, particularly with diffusion models facilitating high-quality image synthesis from textual descriptions. However, these models often struggle with achieving…

Computer Vision and Pattern Recognition · Computer Science 2024-12-30 Lunhao Duan , Shanshan Zhao , Wenjun Yan , Yinglun Li , Qing-Guo Chen , Zhao Xu , Weihua Luo , Kaifu Zhang , Mingming Gong , Gui-Song Xia

In recent years, event cameras have gained significant attention due to their bio-inspired properties, such as high temporal resolution and high dynamic range. However, obtaining large-scale labeled ground-truth data for event-based vision…

Computer Vision and Pattern Recognition · Computer Science 2025-12-01 Yixuan Hu , Yuxuan Xue , Simon Klenk , Daniel Cremers , Gerard Pons-Moll

Recently, image-to-video (I2V) diffusion models have demonstrated impressive scene understanding and generative quality, incorporating image conditions to guide generation. However, these models primarily animate static images without…

Computer Vision and Pattern Recognition · Computer Science 2026-05-29 Luis Denninger , Sina Mokhtarzadeh Azar , Juergen Gall

Video frame interpolation (VFI) in scenarios with large motion remains challenging due to motion ambiguity between frames. While event cameras can capture high temporal resolution motion information, existing event-based VFI methods…

Computer Vision and Pattern Recognition · Computer Science 2025-03-27 Ziran Zhang , Xiaohui Li , Yihao Liu , Yujin Wang , Yueting Chen , Tianfan Xue , Shi Guo

Diffusion models are the current state-of-the-art in image generation, synthesizing high-quality images by breaking down the generation process into many fine-grained denoising steps. Despite their good performance, diffusion models are…

Computer Vision and Pattern Recognition · Computer Science 2023-10-31 Noam Elata , Bahjat Kawar , Tomer Michaeli , Michael Elad

Text-to-image diffusion models produce high quality images but do not offer control over individual instances in the image. We introduce InstanceDiffusion that adds precise instance-level control to text-to-image diffusion models.…

Computer Vision and Pattern Recognition · Computer Science 2024-02-06 Xudong Wang , Trevor Darrell , Sai Saketh Rambhatla , Rohit Girdhar , Ishan Misra

We introduce InstructVid2Vid, an end-to-end diffusion-based methodology for video editing guided by human language instructions. Our approach empowers video manipulation guided by natural language directives, eliminating the need for…

Computer Vision and Pattern Recognition · Computer Science 2024-05-30 Bosheng Qin , Juncheng Li , Siliang Tang , Tat-Seng Chua , Yueting Zhuang

Diffusion model has demonstrated remarkable capability in video generation, which further sparks interest in introducing trajectory control into the generation process. While existing works mainly focus on training-based methods (e.g.,…

Computer Vision and Pattern Recognition · Computer Science 2024-06-25 Haonan Qiu , Zhaoxi Chen , Zhouxia Wang , Yingqing He , Menghan Xia , Ziwei Liu

Image-to-Video (I2V) generation aims to synthesize a video clip according to a given image and condition (e.g., text). The key challenge of this task lies in simultaneously generating natural motions while preserving the original appearance…

Computer Vision and Pattern Recognition · Computer Science 2025-03-04 Jie Tian , Xiaoye Qu , Zhenyi Lu , Wei Wei , Sichen Liu , Yu Cheng

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

Recently, the multimedia community has witnessed the rise of diffusion models trained on large-scale multi-modal data for visual content creation, particularly in the field of text-to-image generation. In this paper, we propose a new task…

Computer Vision and Pattern Recognition · Computer Science 2023-11-10 Jingwen Chen , Yingwei Pan , Ting Yao , Tao Mei

In-domain generation aims to perform a variety of tasks within a specific domain, such as unconditional generation, text-to-image, image editing, 3D generation, and more. Early research typically required training specialized generators for…

Computer Vision and Pattern Recognition · Computer Science 2025-03-21 Pu Cao , Feng Zhou , Lu Yang , Tianrui Huang , Qing Song

Camera control is crucial for generating expressive and cinematic videos. Existing methods rely on explicit sequences of camera parameters as control conditions, which can be cumbersome for users to construct, particularly for intricate…

Computer Vision and Pattern Recognition · Computer Science 2025-06-04 Yawen Luo , Jianhong Bai , Xiaoyu Shi , Menghan Xia , Xintao Wang , Pengfei Wan , Di Zhang , Kun Gai , Tianfan Xue

Recent advances in diffusion models have significantly improved text-to-face generation, but achieving fine-grained control over facial features remains a challenge. Existing methods often require training additional modules to handle…

Computer Vision and Pattern Recognition · Computer Science 2025-05-26 Liang Shi , Yun Fu

Perceptual studies demonstrate that conditional diffusion models excel at reconstructing video content aligned with human visual perception. Building on this insight, we propose a video compression framework that leverages conditional…

Computer Vision and Pattern Recognition · Computer Science 2025-09-26 Fangqiu Yi , Jingyu Xu , Jiawei Shao , Chi Zhang , Xuelong Li

We introduce a framework that enables both multi-view character consistency and 3D camera control in video diffusion models through a novel customization data pipeline. We train the character consistency component with recorded volumetric…

Computer Vision and Pattern Recognition · Computer Science 2025-10-17 Yuancheng Xu , Wenqi Xian , Li Ma , Julien Philip , Ahmet Levent Taşel , Yiwei Zhao , Ryan Burgert , Mingming He , Oliver Hermann , Oliver Pilarski , Rahul Garg , Paul Debevec , Ning Yu

EasyRead pictograms are simple, visually clear images that represent specific concepts and support comprehension for people with intellectual disabilities, low literacy, or language barriers. The large-scale production of EasyRead content…

Human-Computer Interaction · Computer Science 2026-03-17 Nicolas Dickenmann , Yanis Merzouki , Sonia Laguna , Thy Nowak-Tran , Emanuele Palumbo , Julia E. Vogt , Gerda Binder

Creating a vivid video from the event or scenario in our imagination is a truly fascinating experience. Recent advancements in text-to-video synthesis have unveiled the potential to achieve this with prompts only. While text is convenient…

Computer Vision and Pattern Recognition · Computer Science 2023-06-02 Jinbo Xing , Menghan Xia , Yuxin Liu , Yuechen Zhang , Yong Zhang , Yingqing He , Hanyuan Liu , Haoxin Chen , Xiaodong Cun , Xintao Wang , Ying Shan , Tien-Tsin Wong

Conditional diffusion models have exhibited superior performance in high-fidelity text-guided visual generation and editing. Nevertheless, prevailing text-guided visual diffusion models primarily focus on incorporating text-visual…

Computer Vision and Pattern Recognition · Computer Science 2024-06-05 Ling Yang , Zhilong Zhang , Zhaochen Yu , Jingwei Liu , Minkai Xu , Stefano Ermon , Bin Cui

The primary axes of interest in image-generating diffusion models are image quality, the amount of variation in the results, and how well the results align with a given condition, e.g., a class label or a text prompt. The popular…

Computer Vision and Pattern Recognition · Computer Science 2024-12-20 Tero Karras , Miika Aittala , Tuomas Kynkäänniemi , Jaakko Lehtinen , Timo Aila , Samuli Laine