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Real-time free-viewpoint rendering requires balancing multi-camera redundancy with the latency constraints of interactive applications. We address this challenge by combining lightweight geometry with learning and propose 3DTV, a…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Stefan Schulz , Fernando Edelstein , Hannah Dröge , Matthias B. Hullin , Markus Plack

3D asset generation is getting massive amounts of attention, inspired by the recent success of text-guided 2D content creation. Existing text-to-3D methods use pretrained text-to-image diffusion models in an optimization problem or…

Computer Vision and Pattern Recognition · Computer Science 2024-07-30 Lukas Höllein , Aljaž Božič , Norman Müller , David Novotny , Hung-Yu Tseng , Christian Richardt , Michael Zollhöfer , Matthias Nießner

With the advent of depth-to-image diffusion models, text-guided generation, editing, and transfer of realistic textures are no longer difficult. However, due to the limitations of pre-trained diffusion models, they can only create…

Computer Vision and Pattern Recognition · Computer Science 2023-05-11 Zhibin Tang , Tiantong He

Probabilistic denoising diffusion models (DDMs) have set a new standard for 2D image generation. Extending DDMs for 3D content creation is an active field of research. Here, we propose TetraDiffusion, a diffusion model that operates on a…

Computer Vision and Pattern Recognition · Computer Science 2024-08-12 Nikolai Kalischek , Torben Peters , Jan D. Wegner , Konrad Schindler

In this paper, we present TEXTure, a novel method for text-guided generation, editing, and transfer of textures for 3D shapes. Leveraging a pretrained depth-to-image diffusion model, TEXTure applies an iterative scheme that paints a 3D…

Computer Vision and Pattern Recognition · Computer Science 2023-02-06 Elad Richardson , Gal Metzer , Yuval Alaluf , Raja Giryes , Daniel Cohen-Or

Recent advancements in diffusion techniques have propelled image and video generation to unprecedented levels of quality, significantly accelerating the deployment and application of generative AI. However, 3D shape generation technology…

Computer Vision and Pattern Recognition · Computer Science 2025-03-28 Yangguang Li , Zi-Xin Zou , Zexiang Liu , Dehu Wang , Yuan Liang , Zhipeng Yu , Xingchao Liu , Yuan-Chen Guo , Ding Liang , Wanli Ouyang , Yan-Pei Cao

In this paper, we introduce Topology Sculptor, Shape Refiner (TSSR), a novel method for generating high-quality, artist-style 3D meshes based on Discrete Diffusion Models (DDMs). Our primary motivation for TSSR is to achieve highly accurate…

Computer Vision and Pattern Recognition · Computer Science 2025-10-28 Kaiyu Song , Hanjiang Lai , Yaqing Zhang , Chuangjian Cai , Yan Pan Kun Yue , Jian Yin

Recently, talking-face video generation has received considerable attention. So far most methods generate results with neutral expressions or expressions that are implicitly determined by neural networks in an uncontrollable way. In this…

Computer Vision and Pattern Recognition · Computer Science 2022-04-14 Zipeng Ye , Zhiyao Sun , Yu-Hui Wen , Yanan Sun , Tian Lv , Ran Yi , Yong-Jin Liu

Recent years have witnessed remarkable progress in multi-view diffusion models for 3D content creation. However, there remains a significant gap in image quality and prompt-following ability compared to 2D diffusion models. A critical…

Computer Vision and Pattern Recognition · Computer Science 2024-10-04 Zeyi Sun , Tong Wu , Pan Zhang , Yuhang Zang , Xiaoyi Dong , Yuanjun Xiong , Dahua Lin , Jiaqi Wang

Recent advancements in diffusion models have set new benchmarks in image and video generation, enabling realistic visual synthesis across single- and multi-frame contexts. However, these models still struggle with efficiently and explicitly…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Qihang Zhang , Shuangfei Zhai , Miguel Angel Bautista , Kevin Miao , Alexander Toshev , Joshua Susskind , Jiatao Gu

Understanding and predicting dynamics of the physical world can enhance a robot's ability to plan and interact effectively in complex environments. While recent video generation models have shown strong potential in modeling dynamic scenes,…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Zeyi Liu , Shuang Li , Eric Cousineau , Siyuan Feng , Benjamin Burchfiel , Shuran Song

Prevailing 3D texture generation methods, which often rely on multi-view fusion, are frequently hindered by inter-view inconsistencies and incomplete coverage of complex surfaces, limiting the fidelity and completeness of the generated…

Computer Vision and Pattern Recognition · Computer Science 2025-12-03 Yifei Zeng , Yajie Bao , Jiachen Qian , Shuang Wu , Youtian Lin , Hao Zhu , Buyu Li , Feihu Zhang , Xun Cao , Yao Yao

Generating high-fidelity upper-body 3D avatars from one-shot input image remains a significant challenge. Current 3D avatar generation methods, which rely on large reconstruction models, are fast and capable of producing stable body…

Computer Vision and Pattern Recognition · Computer Science 2025-12-10 Fan Yang , Heyuan Li , Peihao Li , Weihao Yuan , Lingteng Qiu , Chaoyue Song , Cheng Chen , Yisheng He , Shifeng Zhang , Xiaoguang Han , Steven Hoi , Guosheng Lin

The growing adoption of XR devices has fueled strong demand for high-quality stereo video, yet its production remains costly and artifact-prone. To address this challenge, we present StereoWorld, an end-to-end framework that repurposes a…

Computer Vision and Pattern Recognition · Computer Science 2025-12-12 Ke Xing , Xiaojie Jin , Longfei Li , Yuyang Yin , Hanwen Liang , Guixun Luo , Chen Fang , Jue Wang , Konstantinos N. Plataniotis , Yao Zhao , Yunchao Wei

Recent progress in image and video synthesis has inspired their use in advancing 3D scene generation. However, we observe that text-to-image and -video approaches struggle to maintain scene- and object-level consistency beyond a limited…

Computer Vision and Pattern Recognition · Computer Science 2026-03-26 Manuel-Andreas Schneider , Angela Dai

Video diffusion models generate high-quality and diverse worlds; however, individual frames often lack 3D consistency across the output sequence, which makes the reconstruction of 3D worlds difficult. To this end, we propose a new method…

Computer Vision and Pattern Recognition · Computer Science 2026-03-19 Lukas Höllein , Matthias Nießner

Three-dimensional content generation has progressed from producing isolated, visually plausible shapes to constructing structured assets that can be deployed in real-time interactive environments. This trajectory is driven by converging…

Graphics · Computer Science 2026-05-12 Jiafeng Wu , Zhuofan Lou , Jian Liu , Dazhao Du , Chunchao Guo , Song Guo

In recent years, video generation has seen significant advancements. However, challenges still persist in generating complex motions and interactions. To address these challenges, we introduce ReVision, a plug-and-play framework that…

Computer Vision and Pattern Recognition · Computer Science 2026-01-12 Qihao Liu , Ju He , Qihang Yu , Liang-Chieh Chen , Alan Yuille

Generating high-quality, textured 3D scenes from a single image remains a fundamental challenge in vision and graphics. Recent image-to-3D generators recover reasonable geometry from single views, but their object-centric training limits…

Computer Vision and Pattern Recognition · Computer Science 2025-12-10 Kaizhi Zheng , Yue Fan , Jing Gu , Zishuo Xu , Xuehai He , Xin Eric Wang

Diffusion-based methods have achieved prominent success in generating 2D media. However, accomplishing similar proficiencies for scene-level mesh texturing in 3D spatial applications, e.g., XR/VR, remains constrained, primarily due to the…

Computer Vision and Pattern Recognition · Computer Science 2023-10-23 Bangbang Yang , Wenqi Dong , Lin Ma , Wenbo Hu , Xiao Liu , Zhaopeng Cui , Yuewen Ma
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