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We address the challenge of relighting a single image or video, a task that demands precise scene intrinsic understanding and high-quality light transport synthesis. Existing end-to-end relighting models are often limited by the scarcity of…

Computer Vision and Pattern Recognition · Computer Science 2025-06-19 Kai He , Ruofan Liang , Jacob Munkberg , Jon Hasselgren , Nandita Vijaykumar , Alexander Keller , Sanja Fidler , Igor Gilitschenski , Zan Gojcic , Zian Wang

Capitalizing on the recent advances in image generation models, existing controllable face image synthesis methods are able to generate high-fidelity images with some levels of controllability, e.g., controlling the shapes, expressions,…

Computer Vision and Pattern Recognition · Computer Science 2023-10-31 Keqiang Sun , Shangzhe Wu , Ning Zhang , Zhaoyang Huang , Quan Wang , Hongsheng Li

Video editing increasingly demands the ability to incorporate specific real-world instances into existing footage, yet current approaches fundamentally fail to capture the unique visual characteristics of particular subjects and ensure…

Computer Vision and Pattern Recognition · Computer Science 2025-03-11 Shaobin Zhuang , Zhipeng Huang , Binxin Yang , Ying Zhang , Fangyikang Wang , Canmiao Fu , Chong Sun , Zheng-Jun Zha , Chen Li , Yali Wang

General-purpose audio representations have proven effective across diverse music information retrieval applications, yet their utility in intelligent music production remains limited by insufficient understanding of audio effects (Fx).…

Traditional 3D content creation tools empower users to bring their imagination to life by giving them direct control over a scene's geometry, appearance, motion, and camera path. Creating computer-generated videos, however, is a tedious…

Computer Vision and Pattern Recognition · Computer Science 2023-12-05 Shengqu Cai , Duygu Ceylan , Matheus Gadelha , Chun-Hao Paul Huang , Tuanfeng Yang Wang , Gordon Wetzstein

Image generation abilities of text-to-image diffusion models have significantly advanced, yielding highly photo-realistic images from descriptive text and increasing the viability of leveraging synthetic images to train computer vision…

Computer Vision and Pattern Recognition · Computer Science 2025-02-10 Jiahui Chen , Amy Zhang , Adriana Romero-Soriano

We introduce the first generative model capable of simultaneous multi-object compositing, guided by both text and layout. Our model allows for the addition of multiple objects within a scene, capturing a range of interactions from simple…

Computer Vision and Pattern Recognition · Computer Science 2025-02-10 Gemma Canet Tarrés , Zhe Lin , Zhifei Zhang , He Zhang , Andrew Gilbert , John Collomosse , Soo Ye Kim

We present a method for relighting 3D reconstructions of large room-scale environments. Existing solutions for 3D scene relighting often require solving under-determined or ill-conditioned inverse rendering problems, and are as such unable…

Computer Vision and Pattern Recognition · Computer Science 2026-01-30 Xiaoyan Xing , Philipp Henzler , Junhwa Hur , Runze Li , Jonathan T. Barron , Pratul P. Srinivasan , Dor Verbin

Recent advances in diffusion-based video generation have opened new possibilities for controllable video editing, yet realistic video object insertion (VOI) remains challenging due to limited 4D scene understanding and inadequate handling…

Computer Vision and Pattern Recognition · Computer Science 2025-12-22 Hoiyeong Jin , Hyojin Jang , Jeongho Kim , Junha Hyung , Kinam Kim , Dongjin Kim , Huijin Choi , Hyeonji Kim , Jaegul Choo

Video Frame Interpolation synthesizes non-existent images between adjacent frames, with the aim of providing a smooth and consistent visual experience. Two approaches for solving this challenging task are optical flow based and kernel-based…

Computer Vision and Pattern Recognition · Computer Science 2021-05-13 Xi Li , Meng Cao , Yingying Tang , Scott Johnston , Zhendong Hong , Huimin Ma , Jiulong Shan

Recent advances in video generation have outpaced progress in video editing, which remains constrained by several limiting factors, namely: (a) the task's dependency on supervision severely limits generality, (b) an unnecessary artificial…

Computer Vision and Pattern Recognition · Computer Science 2025-03-19 Harold Haodong Chen , Harry Yang , Ser-Nam Lim

Inpainting algorithms have achieved remarkable progress in removing objects from images, yet still face two challenges: 1) struggle to handle the object's visual effects such as shadow and reflection; 2) easily generate shape-like artifacts…

Computer Vision and Pattern Recognition · Computer Science 2025-03-12 Runpu Wei , Zijin Yin , Shuo Zhang , Lanxiang Zhou , Xueyi Wang , Chao Ban , Tianwei Cao , Hao Sun , Zhongjiang He , Kongming Liang , Zhanyu Ma

Recent advances in Video Foundation Models (VFMs) have revolutionized human-centric video synthesis, yet fine-grained and independent editing of subjects and scenes remains a critical challenge. Recent attempts to incorporate richer…

Computer Vision and Pattern Recognition · Computer Science 2026-04-02 Fengyuan Yang , Luying Huang , Jiazhi Guan , Quanwei Yang , Dongwei Pan , Jianglin Fu , Haocheng Feng , Wei He , Kaisiyuan Wang , Hang Zhou , Angela Yao

We present a new, fast and flexible pipeline for indoor scene synthesis that is based on deep convolutional generative models. Our method operates on a top-down image-based representation, and inserts objects iteratively into the scene by…

Computer Vision and Pattern Recognition · Computer Science 2018-12-03 Daniel Ritchie , Kai Wang , Yu-an Lin

Generalizing deepfake detection to unseen manipulations remains a key challenge. A recent approach to tackle this issue is to train a network with pristine face images that have been manipulated with hand-crafted artifacts to extract more…

Computer Vision and Pattern Recognition · Computer Science 2026-04-13 Alejandro Cobo , Roberto Valle , José Miguel Buenaposada , Luis Baumela

Generating long-form storytelling videos with consistent visual narratives remains a significant challenge in video synthesis. We present a novel framework, dataset, and a model that address three critical limitations: background…

Recent generative data augmentation methods conditioned on both image and text prompts struggle to balance between fidelity and diversity, as it is challenging to preserve essential image details while aligning with varied text prompts.…

Computer Vision and Pattern Recognition · Computer Science 2025-10-20 Tianchen Zhao , Xuanbai Chen , Zhihua Li , Jun Fang , Dongsheng An , Xiang Xu , Zhuowen Tu , Yifan Xing

Currently, various studies have been exploring generation of long videos. However, the generated frames in these videos often exhibit jitter and noise. Therefore, in order to generate the videos without these noise, we propose a novel…

Computer Vision and Pattern Recognition · Computer Science 2024-03-12 Chaoyi Wang , Yaozhe Song , Yafeng Zhang , Jun Pei , Lijie Xia , Jianpo Liu

Diffusion generative models have recently greatly improved the power of text-conditioned image generation. Existing image generation models mainly include text conditional diffusion model and cross-modal guided diffusion model, which are…

Computer Vision and Pattern Recognition · Computer Science 2022-11-04 Wei Li , Xue Xu , Xinyan Xiao , Jiachen Liu , Hu Yang , Guohao Li , Zhanpeng Wang , Zhifan Feng , Qiaoqiao She , Yajuan Lyu , Hua Wu

Recent large-scale generative models learned on big data are capable of synthesizing incredible images yet suffer from limited controllability. This work offers a new generation paradigm that allows flexible control of the output image,…

Computer Vision and Pattern Recognition · Computer Science 2023-02-23 Lianghua Huang , Di Chen , Yu Liu , Yujun Shen , Deli Zhao , Jingren Zhou
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