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We present a novel framework for rectifying occlusions and distortions in degraded texture samples from natural images. Traditional texture synthesis approaches focus on generating textures from pristine samples, which necessitate…

Graphics · Computer Science 2023-09-27 Guoqing Hao , Satoshi Iizuka , Kensho Hara , Edgar Simo-Serra , Hirokatsu Kataoka , Kazuhiro Fukui

Text-based diffusion models have exhibited remarkable success in generation and editing, showing great promise for enhancing visual content with their generative prior. However, applying these models to video super-resolution remains…

Computer Vision and Pattern Recognition · Computer Science 2023-12-12 Shangchen Zhou , Peiqing Yang , Jianyi Wang , Yihang Luo , Chen Change Loy

Novel view synthesis from a single image has recently attracted a lot of attention, and it has been primarily advanced by 3D deep learning and rendering techniques. However, most work is still limited by synthesizing new views within…

Computer Vision and Pattern Recognition · Computer Science 2022-03-18 Xuanchi Ren , Xiaolong Wang

Recent progress in 3D reconstruction has enabled realistic 3D models from dense image captures, yet challenges persist with sparse views, often leading to artifacts in unseen areas. Recent works leverage Video Diffusion Models (VDMs) to…

Computer Vision and Pattern Recognition · Computer Science 2025-08-11 Wenbin Teng , Gonglin Chen , Haiwei Chen , Yajie Zhao

The pose-guided person image generation task requires synthesizing photorealistic images of humans in arbitrary poses. The existing approaches use generative adversarial networks that do not necessarily maintain realistic textures or need…

Computer Vision and Pattern Recognition · Computer Science 2023-03-02 Ankan Kumar Bhunia , Salman Khan , Hisham Cholakkal , Rao Muhammad Anwer , Jorma Laaksonen , Mubarak Shah , Fahad Shahbaz Khan

The advancement of 4D (i.e., sequential 3D) generation opens up new possibilities for lifelike experiences in various applications, where users can explore dynamic objects or characters from any viewpoint. Meanwhile, video generative models…

Graphics · Computer Science 2025-04-08 Yikai Wang , Guangce Liu , Xinzhou Wang , Zilong Chen , Jiafang Li , Xin Liang , Fuchun Sun , Jun Zhu

Latent diffusion models (LDMs) dominate high-quality image generation, yet integrating representation learning with generative modeling remains a challenge. We introduce a novel generative image modeling framework that seamlessly bridges…

Computer Vision and Pattern Recognition · Computer Science 2026-01-23 Theodoros Kouzelis , Efstathios Karypidis , Ioannis Kakogeorgiou , Spyros Gidaris , Nikos Komodakis

We present a new approach for synthesizing novel views of people in new poses. Our novel differentiable renderer enables the synthesis of highly realistic images from any viewpoint. Rather than operating over mesh-based structures, our…

Computer Vision and Pattern Recognition · Computer Science 2023-03-29 Guillaume Rochette , Chris Russell , Richard Bowden

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

We study the problem of synthesizing a long-term dynamic video from only a single image. This is challenging since it requires consistent visual content movements given large camera motions. Existing methods either hallucinate inconsistent…

Computer Vision and Pattern Recognition · Computer Science 2023-08-22 Liao Shen , Xingyi Li , Huiqiang Sun , Juewen Peng , Ke Xian , Zhiguo Cao , Guosheng Lin

Given a single image of a 3D object, this paper proposes a novel method (named ConsistNet) that is able to generate multiple images of the same object, as if seen they are captured from different viewpoints, while the 3D (multi-view)…

Computer Vision and Pattern Recognition · Computer Science 2023-10-17 Jiayu Yang , Ziang Cheng , Yunfei Duan , Pan Ji , Hongdong Li

The recent success of pre-trained diffusion models unlocks the possibility of the automatic generation of textures for arbitrary 3D meshes in the wild. However, these models are trained in the screen space, while converting them to a…

Computer Vision and Pattern Recognition · Computer Science 2024-06-28 Hongkun Zhang , Zherong Pan , Congyi Zhang , Lifeng Zhu , Xifeng Gao

Video generation models have made significant progress in generating realistic content, enabling applications in simulation, gaming, and film making. However, current generated videos still contain visual artifacts arising from 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-11-25 Duolikun Danier , Ge Gao , Steven McDonagh , Changjian Li , Hakan Bilen , Oisin Mac Aodha

Recent advancements in dynamic 3D scene reconstruction have shown promising results, enabling high-fidelity 3D novel view synthesis with improved temporal consistency. Among these, 4D Gaussian Splatting (4DGS) has emerged as an appealing…

Computer Vision and Pattern Recognition · Computer Science 2025-05-20 Seungjun Oh , Younggeun Lee , Hyejin Jeon , Eunbyung Park

Generating consistent ground-view images from satellite imagery is challenging, primarily due to the large discrepancies in viewing angles and resolution between satellite and ground-level domains. Previous efforts mainly concentrated on…

Computer Vision and Pattern Recognition · Computer Science 2025-04-23 Ningli Xu , Rongjun Qin

Visual synthesis has recently seen significant leaps in performance, largely due to breakthroughs in generative models. Diffusion models have been a key enabler, as they excel in image diversity. However, this comes at the cost of slow…

Computer Vision and Pattern Recognition · Computer Science 2024-12-05 Johannes Schusterbauer , Ming Gui , Pingchuan Ma , Nick Stracke , Stefan A. Baumann , Vincent Tao Hu , Björn Ommer

Recent advances in diffusion models have revolutionized video generation, offering superior temporal consistency and visual quality compared to traditional generative adversarial networks-based approaches. While this emerging field shows…

Computer Vision and Pattern Recognition · Computer Science 2026-02-11 Yimu Wang , Xuye Liu , Wei Pang , Li Ma , Shuai Yuan , Paul Debevec , Ning Yu

While recent research has progressively overcome the low-resolution constraint of one-shot face video re-enactment with the help of StyleGAN's high-fidelity portrait generation, these approaches rely on at least one of the following:…

Computer Vision and Pattern Recognition · Computer Science 2023-02-16 Trevine Oorloff , Yaser Yacoob

Generating 4D scenes from a single-view video is inherently ill-posed: a single viewpoint lacks the information needed to recover a complete, dynamic scene with full coverage. Existing methods are typically limited to monocular videos,…

Computer Vision and Pattern Recognition · Computer Science 2026-05-26 Tingxi Chen , Ke Hao , Yabo Chen , Zhengxue Cheng , Rong Xie , Li Song , Haibin Huang , Chi Zhang , Xuelong Li

Recently, diffusion models have made remarkable progress in text-to-image (T2I) generation, synthesizing images with high fidelity and diverse contents. Despite this advancement, latent space smoothness within diffusion models remains…

Computer Vision and Pattern Recognition · Computer Science 2023-12-08 Jiayi Guo , Xingqian Xu , Yifan Pu , Zanlin Ni , Chaofei Wang , Manushree Vasu , Shiji Song , Gao Huang , Humphrey Shi
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