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Existing industrial 3D garment meshes already cover most real-world clothing geometries, yet their texture diversity remains limited. To acquire more realistic textures, generative methods are often used to extract Physically-based…

Computer Vision and Pattern Recognition · Computer Science 2026-03-16 Hui Shan , Ming Li , Haitao Yang , Kai Zheng , Sizhe Zheng , Yanwei Fu , Xiangru Huang

Achieving physically consistent image editing remains a significant challenge in computer vision. Existing image editing methods typically rely on neural networks, which struggle to accurately handle shadows and refractions. Conversely,…

Computer Vision and Pattern Recognition · Computer Science 2026-05-13 Lezhong Wang , Duc Minh Tran , Ruiqi Cui , Thomson TG , Anders Bjorholm Dahl , Siavash Arjomand Bigdeli , Jeppe Revall Frisvad , Manmohan Chandraker

Full-body Human inverse rendering based on physically-based rendering aims to acquire high-quality materials, which helps achieve photo-realistic rendering under arbitrary illuminations. This task requires estimating multiple material maps…

Computer Vision and Pattern Recognition · Computer Science 2025-07-25 Yu Jiang , Jiahao Xia , Jiongming Qin , Yusen Wang , Tuo Cao , Chunxia Xiao

We introduce Artifact-Based Rendering (ABR), a framework of tools, algorithms, and processes that makes it possible to produce real, data-driven 3D scientific visualizations with a visual language derived entirely from colors, lines,…

Digital human avatars aim to simulate the dynamic appearance of humans in virtual environments, enabling immersive experiences across gaming, film, virtual reality, and more. However, the conventional process for creating and animating…

Computer Vision and Pattern Recognition · Computer Science 2025-10-15 Felix Taubner , Ruihang Zhang , Mathieu Tuli , Sherwin Bahmani , David B. Lindell

Recently, the surge of efficient and automated 3D AI-generated content (AIGC) methods has increasingly illuminated the path of transforming human imagination into complex 3D structures. However, the automated generation of 3D content is…

Graphics · Computer Science 2024-12-20 Pei Chen , Fudong Wang , Yixuan Tong , Jingdong Chen , Ming Yang , Minghui Yang

Multi-view inverse rendering aims to recover geometry, materials, and illumination consistently across multiple viewpoints. When applied to multi-view images, existing single-view approaches often ignore cross-view relationships, leading to…

Computer Vision and Pattern Recognition · Computer Science 2025-12-30 Xiangzuo Wu , Chengwei Ren , Jun Zhou , Xiu Li , Yuan Liu

Learning-based 3D reconstruction methods have shown impressive results. However, most methods require 3D supervision which is often hard to obtain for real-world datasets. Recently, several works have proposed differentiable rendering…

Computer Vision and Pattern Recognition · Computer Science 2020-03-24 Michael Niemeyer , Lars Mescheder , Michael Oechsle , Andreas Geiger

3D texture generation is receiving increasing attention, as it enables the creation of realistic and aesthetic texture materials for untextured 3D meshes. However, existing 3D texture generation methods are limited to producing only a few…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Zhiyuan Zhang , Zijian Zhou , Linjun Li , Long Chen , Hao Tang , Yichen Gong

The lack of labeled datasets in 3D vision for surgical scenes inhibits the development of robust 3D reconstruction algorithms in the medical domain. Despite the popularity of Neural Radiance Fields and 3D Gaussian Splatting in the general…

Computer Vision and Pattern Recognition · Computer Science 2025-03-03 John J. Han , Jie Ying Wu

Interactive volume visualization using a mixed reality (MR) system helps provide users with an intuitive spatial perception of volumetric data. Due to sophisticated requirements of user interaction and vision when using MR head-mounted…

Graphics · Computer Science 2023-09-06 Haojie Cheng , Chunxiao Xu , Xujing Chen , Zhenxin Chen , Jiajun Wang , Lingxiao Zhao

Reward design is of great importance for solving complex tasks with reinforcement learning. Recent studies have explored using image-text similarity produced by vision-language models (VLMs) to augment rewards of a task with visual…

Computer Vision and Pattern Recognition · Computer Science 2026-03-03 Lirui Luo , Guoxi Zhang , Hongming Xu , Yaodong Yang , Cong Fang , Qing Li

In this work, we address a challenge in video inpainting: reconstructing occluded regions in dynamic, real-world scenarios. Motivated by the need for continuous human motion monitoring in healthcare settings, where facial features are…

Computer Vision and Pattern Recognition · Computer Science 2024-12-02 Zheyan Zhang , Diego Klabjan , Renee CB Manworren

While autoregressive Large Vision-Language Models (LVLMs) demonstrate remarkable proficiency in multimodal tasks, they face a "Visual Signal Dilution" phenomenon, where the accumulation of textual history expands the attention partition…

Computer Vision and Pattern Recognition · Computer Science 2026-05-11 Siyuan Huang , Xiaoye Qu , Yafu Li , Tong Zhu , Zefeng He , Muxin Fu , Daizong Liu , Wei-Long Zheng , Yu Cheng

While recent 3D generative models can produce high-quality texture images, they often fail to capture human preferences or meet task-specific requirements. Moreover, a core challenge in the 3D texture generation domain is that most existing…

Computer Vision and Pattern Recognition · Computer Science 2025-12-10 AmirHossein Zamani , Tianhao Xie , Amir G. Aghdam , Tiberiu Popa , Eugene Belilovsky

We present MatDecompSDF, a novel framework for recovering high-fidelity 3D shapes and decomposing their physically-based material properties from multi-view images. The core challenge of inverse rendering lies in the ill-posed…

Computer Vision and Pattern Recognition · Computer Science 2025-12-30 Chengyu Wang , Isabella Bennett , Henry Scott , Liang Zhang , Mei Chen , Hao Li , Rui Zhao

Generating high-quality textures for 3D assets is a challenging task. Existing multiview texture generation methods suffer from the multiview inconsistency and missing textures on unseen parts, while UV inpainting texture methods do not…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Zheng Zhang , Qinchuan Zhang , Yuteng Ye , Zhi Chen , Penglei Ji , Mengfei Li , Wenxiao Zhang , Yuan Liu

Manual modeling of material parameters and 3D geometry is a time consuming yet essential task in the gaming and film industries. While recent advances in 3D reconstruction have enabled accurate approximations of scene geometry and…

Computer Vision and Pattern Recognition · Computer Science 2025-12-23 Philipp Langsteiner , Jan-Niklas Dihlmann , Hendrik P. A. Lensch

Recent advances in 3D avatar generation have gained significant attentions. These breakthroughs aim to produce more realistic animatable avatars, narrowing the gap between virtual and real-world experiences. Most of existing works employ…

Computer Vision and Pattern Recognition · Computer Science 2024-10-01 Mingyuan Zhou , Rakib Hyder , Ziwei Xuan , Guojun Qi

We present Material Anything, a fully-automated, unified diffusion framework designed to generate physically-based materials for 3D objects. Unlike existing methods that rely on complex pipelines or case-specific optimizations, Material…

Computer Vision and Pattern Recognition · Computer Science 2024-11-25 Xin Huang , Tengfei Wang , Ziwei Liu , Qing Wang