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Modern video generation models like Sora have achieved remarkable success in producing high-quality videos. However, a significant limitation is their inability to offer interactive control to users, a feature that promises to open up…

Computer Vision and Pattern Recognition · Computer Science 2024-04-23 Yash Jain , Anshul Nasery , Vibhav Vineet , Harkirat Behl

We present Stable Video Diffusion - a latent video diffusion model for high-resolution, state-of-the-art text-to-video and image-to-video generation. Recently, latent diffusion models trained for 2D image synthesis have been turned into…

Computer Vision and Pattern Recognition · Computer Science 2023-11-28 Andreas Blattmann , Tim Dockhorn , Sumith Kulal , Daniel Mendelevitch , Maciej Kilian , Dominik Lorenz , Yam Levi , Zion English , Vikram Voleti , Adam Letts , Varun Jampani , Robin Rombach

Character video synthesis aims to produce realistic videos of animatable characters within lifelike scenes. As a fundamental problem in the computer vision and graphics community, 3D works typically require multi-view captures for per-case…

Computer Vision and Pattern Recognition · Computer Science 2025-06-12 Yifang Men , Yuan Yao , Miaomiao Cui , Liefeng Bo

The task of layout-to-image generation involves synthesizing images based on the captions of objects and their spatial positions. Existing methods still struggle in complex layout generation, where common bad cases include object missing,…

Computer Vision and Pattern Recognition · Computer Science 2024-10-21 Bo Cheng , Yuhang Ma , Liebucha Wu , Shanyuan Liu , Ao Ma , Xiaoyu Wu , Dawei Leng , Yuhui Yin

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…

Image composition targets at synthesizing a realistic composite image from a pair of foreground and background images. Recently, generative composition methods are built on large pretrained diffusion models to generate composite images,…

Computer Vision and Pattern Recognition · Computer Science 2023-08-22 Bo Zhang , Yuxuan Duan , Jun Lan , Yan Hong , Huijia Zhu , Weiqiang Wang , Li Niu

The emergence of diffusion models has greatly propelled the progress in image and video generation. Recently, some efforts have been made in controllable video generation, including text-to-video generation and video motion control, among…

Computer Vision and Pattern Recognition · Computer Science 2024-05-02 Teng Hu , Jiangning Zhang , Ran Yi , Yating Wang , Hongrui Huang , Jieyu Weng , Yabiao Wang , Lizhuang Ma

Focus is a cornerstone of photography, yet autofocus systems often fail to capture the intended subject, and users frequently wish to adjust focus after capture. We introduce a novel method for realistic post-capture refocusing using video…

Computer Vision and Pattern Recognition · Computer Science 2025-12-30 SaiKiran Tedla , Zhoutong Zhang , Xuaner Zhang , Shumian Xin

Effective and generalizable control in video generation remains a significant challenge. While many methods rely on ambiguous or task-specific signals, we argue that a fundamental disentanglement of "appearance" and "motion" provides a more…

Computer Vision and Pattern Recognition · Computer Science 2026-02-16 Mingzhi Sheng , Zekai Gu , Peng Li , Cheng Lin , Hao-Xiang Guo , Ying-Cong Chen , Yuan Liu

Stereo video generation has been gaining increasing attention with recent advancements in video diffusion models. However, most existing methods focus on generating 3D stereoscopic videos from monocular 2D videos. These approaches typically…

Computer Vision and Pattern Recognition · Computer Science 2025-06-09 Xingchang Huang , Ashish Kumar Singh , Florian Dubost , Cristina Nader Vasconcelos , Sakar Khattar , Liang Shi , Christian Theobalt , Cengiz Oztireli , Gurprit Singh

High-quality 3D scene generation from a single image is crucial for AR/VR and embodied AI applications. Early approaches struggle to generalize due to reliance on specialized models trained on curated small datasets. While recent…

Computer Vision and Pattern Recognition · Computer Science 2025-12-02 Boshi Tang , Henry Zheng , Rui Huang , Gao Huang

Recent 3D large reconstruction models typically employ a two-stage process, including first generate multi-view images by a multi-view diffusion model, and then utilize a feed-forward model to reconstruct images to 3D content.However,…

Computer Vision and Pattern Recognition · Computer Science 2024-07-30 Zhenyu Tang , Junwu Zhang , Xinhua Cheng , Wangbo Yu , Chaoran Feng , Yatian Pang , Bin Lin , Li Yuan

Recently, methods leveraging diffusion model priors to assist monocular geometric estimation (e.g., depth and normal) have gained significant attention due to their strong generalization ability. However, most existing works focus on…

Computer Vision and Pattern Recognition · Computer Science 2025-06-02 Yang-Tian Sun , Xin Yu , Zehuan Huang , Yi-Hua Huang , Yuan-Chen Guo , Ziyi Yang , Yan-Pei Cao , Xiaojuan Qi

Synthesizing multi-view 3D from one single image is a significant but challenging task. Zero-1-to-3 methods have achieved great success by lifting a 2D latent diffusion model to the 3D scope. The target view image is generated with a…

Computer Vision and Pattern Recognition · Computer Science 2024-08-09 Yabo Chen , Jiemin Fang , Yuyang Huang , Taoran Yi , Xiaopeng Zhang , Lingxi Xie , Xinggang Wang , Wenrui Dai , Hongkai Xiong , Qi Tian

With the development of video generation models has advanced significantly in recent years, we adopt large-scale image-to-video diffusion models for video frame interpolation. We present a conditional encoder designed to adapt an…

Computer Vision and Pattern Recognition · Computer Science 2025-02-18 Luoxu Jin , Hiroshi Watanabe

Recent advancements in diffusion models have significantly improved the realism and generalizability of character-driven animation, enabling the synthesis of high-quality motion from just a single RGB image and a set of driving poses.…

Computer Vision and Pattern Recognition · Computer Science 2025-12-02 Alireza Javanmardi , Pragati Jaiswal , Tewodros Amberbir Habtegebrial , Christen Millerdurai , Shaoxiang Wang , Alain Pagani , Didier Stricker

This paper presents Video-P2P, a novel framework for real-world video editing with cross-attention control. While attention control has proven effective for image editing with pre-trained image generation models, there are currently no…

Computer Vision and Pattern Recognition · Computer Science 2023-03-09 Shaoteng Liu , Yuechen Zhang , Wenbo Li , Zhe Lin , Jiaya Jia

Multi-view generation with camera pose control and prompt-based customization are both essential elements for achieving controllable generative models. However, existing multi-view generation models do not support customization with…

Computer Vision and Pattern Recognition · Computer Science 2026-03-12 Minjung Shin , Hyunin Cho , Sooyeon Go , Jin-Hwa Kim , Youngjung Uh

Controlling both camera motion and object dynamics is essential for coherent and expressive video generation, yet current methods typically handle only one motion type or rely on ambiguous 2D cues that entangle camera-induced parallax with…

Computer Vision and Pattern Recognition · Computer Science 2026-04-16 Guiyu Zhang , Yabo Chen , Xunzhi Xiang , Junchao Huang , Zhongyu Wang , Li Jiang

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