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Related papers: Efficient 3D Content Reconstruction and Generation

200 papers

Aided by text-to-image and text-to-video diffusion models, existing 4D content creation pipelines utilize score distillation sampling to optimize the entire dynamic 3D scene. However, as these pipelines generate 4D content from text or…

Computer Vision and Pattern Recognition · Computer Science 2024-12-05 Yuyang Yin , Dejia Xu , Zhangyang Wang , Yao Zhao , Yunchao Wei

Generative artificial intelligence has recently progressed from static image and video synthesis to 3D content generation, culminating in the emergence of 4D generation-the task of synthesizing temporally coherent dynamic 3D assets guided…

Computer Vision and Pattern Recognition · Computer Science 2025-07-25 Qiaowei Miao , Kehan Li , Jinsheng Quan , Zhiyuan Min , Shaojie Ma , Yichao Xu , Yi Yang , Ping Liu , Yawei Luo

We present Seed3D 2.0, an advanced 3D content generation system built on Seed3D 1.0, with substantial improvements across generation fidelity, simulation-ready capabilities, and application coverage. For geometry, a coarse-to-fine two-stage…

We propose LiteReality, a novel pipeline that converts RGB-D scans of indoor environments into compact, realistic, and interactive 3D virtual replicas. LiteReality not only reconstructs scenes that visually resemble reality but also…

Computer Vision and Pattern Recognition · Computer Science 2026-03-20 Zhening Huang , Xiaoyang Wu , Fangcheng Zhong , Hengshuang Zhao , Matthias Nießner , Joan Lasenby

In this work, we present a novel framework built to simplify 3D asset generation for amateur users. To enable interactive generation, our method supports a variety of input modalities that can be easily provided by a human, including…

Computer Vision and Pattern Recognition · Computer Science 2023-03-23 Yen-Chi Cheng , Hsin-Ying Lee , Sergey Tulyakov , Alexander Schwing , Liangyan Gui

Interactive 3D scenes are increasingly vital for embodied intelligence, yet existing datasets remain limited due to the labor-intensive process of annotating part segmentation, kinematic types, and motion trajectories. We present REACT3D, a…

Computer Vision and Pattern Recognition · Computer Science 2026-04-13 Zhao Huang , Boyang Sun , Alexandros Delitzas , Jiaqi Chen , Marc Pollefeys

While neural 3D reconstruction has advanced substantially, its performance significantly degrades with sparse-view data, which limits its broader applicability, since SfM is often unreliable in sparse-view scenarios where feature matches…

Computer Vision and Pattern Recognition · Computer Science 2025-07-08 Zhiwen Fan , Wenyan Cong , Kairun Wen , Kevin Wang , Jian Zhang , Xinghao Ding , Danfei Xu , Boris Ivanovic , Marco Pavone , Georgios Pavlakos , Zhangyang Wang , Yue Wang

Designing 3D scenes is traditionally a challenging task that demands both artistic expertise and proficiency with complex software. Recent advances in text-to-3D generation have greatly simplified this process by letting users create scenes…

Computer Vision and Pattern Recognition · Computer Science 2025-06-03 Zeqi Gu , Yin Cui , Zhaoshuo Li , Fangyin Wei , Yunhao Ge , Jinwei Gu , Ming-Yu Liu , Abe Davis , Yifan Ding

The recent advances in text and image synthesis show a great promise for the future of generative models in creative fields. However, a less explored area is the one of 3D model generation, with a lot of potential applications to game…

Computer Vision and Pattern Recognition · Computer Science 2023-12-14 Antoine Schnepf , Flavian Vasile , Ugo Tanielian

Advances in generative artificial intelligence have altered multimedia creation, allowing for automatic cinematic video synthesis from text inputs. This work describes a method for creating 60-second cinematic movies incorporating Stable…

Computer Vision and Pattern Recognition · Computer Science 2025-06-13 Sridhar S , Nithin A , Shakeel Rifath , Vasantha Raj

Current image-to-3D approaches suffer from high computational costs and lack scalability for high-resolution outputs. In contrast, we introduce a novel framework to directly generate explicit surface geometry and texture using multi-view 2D…

Computer Vision and Pattern Recognition · Computer Science 2024-11-19 Haoyu Wu , Meher Gitika Karumuri , Chuhang Zou , Seungbae Bang , Yuelong Li , Dimitris Samaras , Sunil Hadap

With the increasing demand for 3D animation, generating high-fidelity, controllable 4D avatars from textual descriptions remains a significant challenge. Despite notable efforts in 4D generative modeling, existing methods exhibit…

Computer Vision and Pattern Recognition · Computer Science 2025-11-21 Eddie Pokming Sheung , Qihao Liu , Wufei Ma , Prakhar Kaushik , Jianwen Xie , Alan Yuille

Generating high-quality 3D objects from textual descriptions remains a challenging problem due to computational cost, the scarcity of 3D data, and complex 3D representations. We introduce Geometry Image Diffusion (GIMDiffusion), a novel…

Computer Vision and Pattern Recognition · Computer Science 2024-09-06 Slava Elizarov , Ciara Rowles , Simon Donné

We propose Flash3D, a method for scene reconstruction and novel view synthesis from a single image which is both very generalisable and efficient. For generalisability, we start from a "foundation" model for monocular depth estimation and…

Computer Vision and Pattern Recognition · Computer Science 2025-06-03 Stanislaw Szymanowicz , Eldar Insafutdinov , Chuanxia Zheng , Dylan Campbell , João F. Henriques , Christian Rupprecht , Andrea Vedaldi

Recent developments in generative models and large-scale datasets have substantially advanced 3D world generation, facilitating a broad range of domains including spatial intelligence, embodied intelligence, and autonomous driving. While…

Computer Vision and Pattern Recognition · Computer Science 2026-05-14 Hanxin Zhu , Cong Wang , Peiyan Tu , Jiayi Luo , Tianyu He , Xin Jin , Zhibo Chen

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

Text-to-3D generation is to craft a 3D object according to a natural language description. This can significantly reduce the workload for manually designing 3D models and provide a more natural way of interaction for users. However, this…

Computer Vision and Pattern Recognition · Computer Science 2023-09-27 Han Yi , Zhedong Zheng , Xiangyu Xu , Tat-seng Chua

For the last decades, the concern of producing convincing facial animation has garnered great interest, that has only been accelerating with the recent explosion of 3D content in both entertainment and professional activities. The use of…

Graphics · Computer Science 2020-10-13 Eloïse Berson , Catherine Soladié , Nicolas Stoiber

Creating large-scale interactive 3D environments is essential for the development of Robotics and Embodied AI research. Current methods, including manual design, procedural generation, diffusion-based scene generation, and large language…

Computer Vision and Pattern Recognition · Computer Science 2024-11-18 Yian Wang , Xiaowen Qiu , Jiageng Liu , Zhehuan Chen , Jiting Cai , Yufei Wang , Tsun-Hsuan Wang , Zhou Xian , Chuang Gan

3D reconstruction is a technique used in computer vision which has a wide range of applications in areas like object recognition, city modelling, virtual reality, physical simulations, video games and special effects. Previously, to perform…

Computer Vision and Pattern Recognition · Computer Science 2017-10-06 Saed Khawaldeh , Tajwar Abrar Aleef , Usama Pervaiz , Vu Hoang Minh , Yeman Brhane Hagos