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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

Despite the recent strides in video generation, state-of-the-art methods still struggle with elements of visual detail. One particularly challenging case is the class of videos in which the intricate motion of the hand coupled with a mostly…

Computer Vision and Pattern Recognition · Computer Science 2025-07-15 Yayuan Li , Zhi Cao , Jason J. Corso

Image diffusion models, trained on massive image collections, have emerged as the most versatile image generator model in terms of quality and diversity. They support inverting real images and conditional (e.g., text) generation, making…

Computer Vision and Pattern Recognition · Computer Science 2023-03-23 Duygu Ceylan , Chun-Hao Paul Huang , Niloy J. Mitra

Recently, diffusion models like StableDiffusion have achieved impressive image generation results. However, the generation process of such diffusion models is uncontrollable, which makes it hard to generate videos with continuous and…

Computer Vision and Pattern Recognition · Computer Science 2023-08-04 Zhihao Hu , Dong Xu

Recent advances in large-scale text-to-image generation models have led to a surge in subject-driven text-to-image generation, which aims to produce customized images that align with textual descriptions while preserving the identity of…

Computer Vision and Pattern Recognition · Computer Science 2025-05-29 Kewen Chen , Xiaobin Hu , Wenqi Ren

Single-view reference-to-video methods often struggle to preserve identity consistency under large facial-angle variations. This limitation naturally motivates the incorporation of multi-view facial references. However, simply introducing…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Bin Hu , Zipeng Qi , Guoxi Huang , Zunnan Xu , Ruicheng Zhang , Chongjie Ye , Jun Zhou , Xiu Li , Jingdong Wang

Advances in diffusion-based video generation models, while significantly improving human animation, poses threats of misuse through the creation of fake videos from a specific person's photo and text prompts. Recent efforts have focused on…

Computer Vision and Pattern Recognition · Computer Science 2026-03-26 Duc Vu , Anh Nguyen , Chi Tran , Anh Tran

Despite the remarkable success of diffusion models in text-to-image generation, their effectiveness in grounded visual editing and compositional control remains challenging. Motivated by advances in self-supervised learning and in-context…

Computer Vision and Pattern Recognition · Computer Science 2025-07-21 Shreya Kadambi , Risheek Garrepalli , Shubhankar Borse , Munawar Hyatt , Fatih Porikli

In this paper, we present CCEdit, a versatile generative video editing framework based on diffusion models. Our approach employs a novel trident network structure that separates structure and appearance control, ensuring precise and…

Computer Vision and Pattern Recognition · Computer Science 2024-04-09 Ruoyu Feng , Wenming Weng , Yanhui Wang , Yuhui Yuan , Jianmin Bao , Chong Luo , Zhibo Chen , Baining Guo

In autonomous driving, vision-centric 3D detection aims to identify 3D objects from images. However, high data collection costs and diverse real-world scenarios limit the scale of training data. Once distribution shifts occur between…

Computer Vision and Pattern Recognition · Computer Science 2025-03-17 Hongbin Lin , Zilu Guo , Yifan Zhang , Shuaicheng Niu , Yafeng Li , Ruimao Zhang , Shuguang Cui , Zhen Li

Customized generation has achieved significant progress in image synthesis, yet personalized video generation remains challenging due to temporal inconsistencies and quality degradation. In this paper, we introduce CustomVideoX, an…

Computer Vision and Pattern Recognition · Computer Science 2025-02-21 D. She , Mushui Liu , Jingxuan Pang , Jin Wang , Zhen Yang , Wanggui He , Guanghao Zhang , Yi Wang , Qihan Huang , Haobin Tang , Yunlong Yu , Siming Fu

Exquisite demand exists for customizing the pretrained large text-to-image model, $\textit{e.g.}$, Stable Diffusion, to generate innovative concepts, such as the users themselves. However, the newly-added concept from previous customization…

Computer Vision and Pattern Recognition · Computer Science 2023-06-02 Ge Yuan , Xiaodong Cun , Yong Zhang , Maomao Li , Chenyang Qi , Xintao Wang , Ying Shan , Huicheng Zheng

Recent advancements in diffusion models have greatly improved the quality and diversity of synthesized content. To harness the expressive power of diffusion models, researchers have explored various controllable mechanisms that allow users…

Computer Vision and Pattern Recognition · Computer Science 2023-04-28 Tsai-Shien Chen , Chieh Hubert Lin , Hung-Yu Tseng , Tsung-Yi Lin , Ming-Hsuan Yang

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

Text-to-image diffusion models produce impressive results but are frustrating tools for artists who desire fine-grained control. For example, a common use case is to create images of a specific instance in novel contexts, i.e.,…

Computer Vision and Pattern Recognition · Computer Science 2024-11-28 Shengqu Cai , Eric Chan , Yunzhi Zhang , Leonidas Guibas , Jiajun Wu , Gordon Wetzstein

Although diffusion models have demonstrated remarkable generative capabilities, existing style transfer techniques often struggle to maintain identity while achieving high-quality stylization. This limitation becomes particularly critical…

Computer Vision and Pattern Recognition · Computer Science 2025-09-30 Mohammad Ali Rezaei , Helia Hajikazem , Saeed Khanehgir , Mahdi Javanmardi

In this paper, we present LaVieID, a novel \underline{l}ocal \underline{a}utoregressive \underline{vi}d\underline{e}o diffusion framework designed to tackle the challenging \underline{id}entity-preserving text-to-video task. The key idea of…

Computer Vision and Pattern Recognition · Computer Science 2025-08-12 Wenhui Song , Hanhui Li , Jiehui Huang , Panwen Hu , Yuhao Cheng , Long Chen , Yiqiang Yan , Xiaodan Liang

Diffusion based video generation has received extensive attention and achieved considerable success within both the academic and industrial communities. However, current efforts are mainly concentrated on single-objective or single-task…

Computer Vision and Pattern Recognition · Computer Science 2024-01-18 Ludan Ruan , Lei Tian , Chuanwei Huang , Xu Zhang , Xinyan Xiao

The generation of sounding videos has seen significant advancements with the advent of diffusion models. However, existing methods often lack the fine-grained control needed to generate viewpoint-specific content from larger, immersive…

Text-to-image diffusion models have shown impressive capabilities in generating realistic visuals from natural-language prompts, yet they often struggle with accurately binding attributes to corresponding objects, especially in prompts…

Computer Vision and Pattern Recognition · Computer Science 2025-05-05 Do Huu Dat , Nam Hyeonu , Po-Yuan Mao , Tae-Hyun Oh