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Generating dynamic 3D object from a single-view video is challenging due to the lack of 4D labeled data. An intuitive approach is to extend previous image-to-3D pipelines by transferring off-the-shelf image generation models such as score…

Computer Vision and Pattern Recognition · Computer Science 2026-01-30 Zijie Pan , Zeyu Yang , Xiatian Zhu , Li Zhang

3D Gaussian splatting enables high-quality novel view synthesis (NVS) at real-time frame rates. However, its quality drops sharply as we depart from the training views. Thus, dense captures are needed to match the high-quality expectations…

Computer Vision and Pattern Recognition · Computer Science 2025-08-06 Tobias Fischer , Samuel Rota Bulò , Yung-Hsu Yang , Nikhil Keetha , Lorenzo Porzi , Norman Müller , Katja Schwarz , Jonathon Luiten , Marc Pollefeys , Peter Kontschieder

Video tokenization procedure is critical for a wide range of video processing tasks. Most existing approaches directly transform video into fixed-grid and patch-wise tokens, which exhibit limited versatility. Spatially, uniformly allocating…

Computer Vision and Pattern Recognition · Computer Science 2025-08-18 Zhenghao Chen , Zicong Chen , Lei Liu , Yiming Wu , Dong Xu

Handling the dynamic environments is a significant research challenge in Visual Simultaneous Localization and Mapping (SLAM). Recent research combines 3D Gaussian Splatting (3DGS) with SLAM to achieve both robust camera pose estimation and…

Computer Vision and Pattern Recognition · Computer Science 2026-04-29 Yunsong Wang , Gim Hee Lee

Dynamic extensions of 3D Gaussian Splatting (3DGS) achieve high-quality reconstructions through neural motion fields, but per-Gaussian neural inference makes these models computationally expensive. Building on DeformableGS, we introduce…

Graphics · Computer Science 2026-03-31 Allen Tu , Haiyang Ying , Alex Hanson , Yonghan Lee , Tom Goldstein , Matthias Zwicker

Recently, 3D Gaussian Splatting (3DGS) has demonstrated excellent ability in small-scale 3D surface reconstruction. However, extending 3DGS to large-scale scenes remains a significant challenge. To address this gap, we propose a novel…

Computer Vision and Pattern Recognition · Computer Science 2024-09-24 YuanZheng Wu , Jin Liu , Shunping Ji

Recovering 3D information from scenes via multi-view stereo reconstruction (MVS) and novel view synthesis (NVS) is inherently challenging, particularly in scenarios involving sparse-view setups. The advent of 3D Gaussian Splatting (3DGS)…

Computer Vision and Pattern Recognition · Computer Science 2025-05-06 Shubhendu Jena , Shishir Reddy Vutukur , Adnane Boukhayma

We introduce DD3G, a formulation that Distills a multi-view Diffusion model (MV-DM) into a 3D Generator using gaussian splatting. DD3G compresses and integrates extensive visual and spatial geometric knowledge from the MV-DM by simulating…

Computer Vision and Pattern Recognition · Computer Science 2025-04-04 Hao Qin , Luyuan Chen , Ming Kong , Mengxu Lu , Qiang Zhu

Recently, 3D Gaussian Splatting has emerged as a prominent research direction owing to its ultrarapid training speed and high-fidelity rendering capabilities. However, the unstructured and irregular nature of Gaussian point clouds poses…

Computer Vision and Pattern Recognition · Computer Science 2026-02-16 Xiao Ren , Yu Liu , Ning An , Jian Cheng , Xin Qiao , He Kong

We study reconstructing and predicting 3D fluid appearance and velocity from a single video. Current methods require multi-view videos for fluid reconstruction. We present FluidNexus, a novel framework that bridges video generation and…

Computer Vision and Pattern Recognition · Computer Science 2025-07-11 Yue Gao , Hong-Xing Yu , Bo Zhu , Jiajun Wu

3D Gaussian splatting (3DGS) has recently demonstrated impressive capabilities in real-time novel view synthesis and 3D reconstruction. However, 3DGS heavily depends on the accurate initialization derived from Structure-from-Motion (SfM)…

Computer Vision and Pattern Recognition · Computer Science 2024-05-29 Jaewoo Jung , Jisang Han , Honggyu An , Jiwon Kang , Seonghoon Park , Seungryong Kim

Reconstructing high-quality 3D models from sparse 2D images has garnered significant attention in computer vision. Recently, 3D Gaussian Splatting (3DGS) has gained prominence due to its explicit representation with efficient training speed…

Computer Vision and Pattern Recognition · Computer Science 2024-12-31 Keng-Wei Chang , Zi-Ming Wang , Shang-Hong Lai

In underwater images, most useful features are occluded by water. The extent of the occlusion depends on imaging geometry and can vary even across a sequence of burst images. As a result, 3D reconstruction methods robust on in-air scenes,…

Computer Vision and Pattern Recognition · Computer Science 2025-11-04 Nir Mualem , Roy Amoyal , Oren Freifeld , Derya Akkaynak

Recent advances in text-to-3D creation integrate the potent prior of Diffusion Models from text-to-image generation into 3D domain. Nevertheless, generating 3D scenes with multiple objects remains challenging. Therefore, we present…

Computer Vision and Pattern Recognition · Computer Science 2025-04-03 Yueming Zhao , Xuening Yuan , Hongyu Yang , Di Huang

Recent advancements in 3D content generation from text or a single image struggle with limited high-quality 3D datasets and inconsistency from 2D multi-view generation. We introduce DiffSplat, a novel 3D generative framework that natively…

Computer Vision and Pattern Recognition · Computer Science 2025-01-29 Chenguo Lin , Panwang Pan , Bangbang Yang , Zeming Li , Yadong Mu

With the rapid advancement of 3D visualization, 3D Gaussian Splatting (3DGS) has emerged as a leading technique for real-time, high-fidelity rendering. While prior research has emphasized algorithmic performance and visual fidelity, the…

Computer Vision and Pattern Recognition · Computer Science 2025-11-12 Zhaolin Wan , Yining Diao , Jingqi Xu , Hao Wang , Zhiyang Li , Xiaopeng Fan , Wangmeng Zuo , Debin Zhao

Photorealistic 3D reconstruction of street scenes is a critical technique for developing real-world simulators for autonomous driving. Despite the efficacy of Neural Radiance Fields (NeRF) for driving scenes, 3D Gaussian Splatting (3DGS)…

Computer Vision and Pattern Recognition · Computer Science 2024-05-31 Nan Huang , Xiaobao Wei , Wenzhao Zheng , Pengju An , Ming Lu , Wei Zhan , Masayoshi Tomizuka , Kurt Keutzer , Shanghang Zhang

The increasing demand for virtual reality applications has highlighted the significance of crafting immersive 3D assets. We present a text-to-3D 360$^{\circ}$ scene generation pipeline that facilitates the creation of comprehensive…

Computer Vision and Pattern Recognition · Computer Science 2024-07-26 Shijie Zhou , Zhiwen Fan , Dejia Xu , Haoran Chang , Pradyumna Chari , Tejas Bharadwaj , Suya You , Zhangyang Wang , Achuta Kadambi

We present a novel method to reconstruct a fluid's 3D density and motion based on just a single sequence of images. This is rendered possible by using powerful physical priors for this strongly under-determined problem. More specifically,…

Graphics · Computer Science 2018-06-20 Marie-Lena Eckert , Wolfgang Heidrich , Nils Thuerey

While dynamic novel view synthesis from 2D videos has seen progress, achieving efficient reconstruction and rendering of dynamic scenes remains a challenging task. In this paper, we introduce Disentangled 4D Gaussian Splatting…

Graphics · Computer Science 2025-10-31 Hao Feng , Hao Sun , Wei Xie , Zhi Zuo , Zhengzhe Liu