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Realistic 3D human generation from text prompts is a desirable yet challenging task. Existing methods optimize 3D representations like mesh or neural fields via score distillation sampling (SDS), which suffers from inadequate fine details…

Computer Vision and Pattern Recognition · Computer Science 2024-03-15 Xian Liu , Xiaohang Zhan , Jiaxiang Tang , Ying Shan , Gang Zeng , Dahua Lin , Xihui Liu , Ziwei Liu

We introduce Drag4D, an interactive framework that integrates object motion control within text-driven 3D scene generation. This framework enables users to define 3D trajectories for the 3D objects generated from a single image, seamlessly…

Computer Vision and Pattern Recognition · Computer Science 2025-09-29 Minjun Kang , Inkyu Shin , Taeyeop Lee , In So Kweon , Kuk-Jin Yoon

Feed-forward based 3D Gaussian Splatting methods have demonstrated exceptional capability in real-time novel view synthesis for human models. However, current approaches are confined to either dense viewpoint configurations or restricted…

Computer Vision and Pattern Recognition · Computer Science 2025-03-13 Yingdong Hu , Zhening Liu , Jiawei Shao , Zehong Lin , Jun Zhang

In this paper, we demonstrate a fully automatic method for converting a still image into a realistic animated looping video. We target scenes with continuous fluid motion, such as flowing water and billowing smoke. Our method relies on the…

Computer Vision and Pattern Recognition · Computer Science 2020-12-01 Aleksander Holynski , Brian Curless , Steven M. Seitz , Richard Szeliski

3D Gaussian Splatting (3DGS) has become a state-of-the-art framework for real-time, high-fidelity novel view synthesis. However, its substantial storage requirements and inherently unstructured representation pose challenges for deployment…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Yuqin Lu , Yang Zhou , Yihua Dai , Guiqing Li , Shengfeng He

Reconstructing dynamic 3D scenes from 2D images and generating diverse views over time is challenging due to scene complexity and temporal dynamics. Despite advancements in neural implicit models, limitations persist: (i) Inadequate Scene…

Computer Vision and Pattern Recognition · Computer Science 2024-02-23 Zeyu Yang , Hongye Yang , Zijie Pan , Li Zhang

We present GaussFusion, a novel approach for improving 3D Gaussian splatting (3DGS) reconstructions in the wild through geometry-informed video generation. GaussFusion mitigates common 3DGS artifacts, including floaters, flickering, and…

Computer Vision and Pattern Recognition · Computer Science 2026-03-31 Liyuan Zhu , Manjunath Narayana , Michal Stary , Will Hutchcroft , Gordon Wetzstein , Iro Armeni

Most 3D Gaussian Splatting (3D-GS) based methods for urban scenes initialize 3D Gaussians directly with 3D LiDAR points, which not only underutilizes LiDAR data capabilities but also overlooks the potential advantages of fusing LiDAR with…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Cheng Zhao , Su Sun , Ruoyu Wang , Yuliang Guo , Jun-Jun Wan , Zhou Huang , Xinyu Huang , Yingjie Victor Chen , Liu Ren

Radiance field methods represent the state of the art in reconstructing complex scenes from multi-view photos. However, these reconstructions often suffer from one or both of the following limitations: First, they typically represent scenes…

Computer Vision and Pattern Recognition · Computer Science 2024-11-25 Chao Wang , Krzysztof Wolski , Bernhard Kerbl , Ana Serrano , Mojtaba Bemana , Hans-Peter Seidel , Karol Myszkowski , Thomas Leimkühler

High-fidelity 3D video reconstruction is essential for enabling real-time rendering of dynamic scenes with realistic motion in virtual and augmented reality (VR/AR). The deformation field paradigm of 3D Gaussian splatting has achieved…

Computer Vision and Pattern Recognition · Computer Science 2025-08-01 Zhenyang Li , Xiaoyang Bai , Tongchen Zhang , Pengfei Shen , Weiwei Xu , Yifan Peng

Synthesizing consistent and photorealistic 3D scenes is an open problem in computer vision. Video diffusion models generate impressive videos but cannot directly synthesize 3D representations, i.e., lack 3D consistency in the generated…

Computer Vision and Pattern Recognition · Computer Science 2025-03-18 Katja Schwarz , Norman Mueller , Peter Kontschieder

We present MVSGaussian, a new generalizable 3D Gaussian representation approach derived from Multi-View Stereo (MVS) that can efficiently reconstruct unseen scenes. Specifically, 1) we leverage MVS to encode geometry-aware Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Tianqi Liu , Guangcong Wang , Shoukang Hu , Liao Shen , Xinyi Ye , Yuhang Zang , Zhiguo Cao , Wei Li , Ziwei Liu

Real objects that inhabit the physical world follow physical laws and thus behave plausibly during interaction with other physical objects. However, current methods that perform 3D reconstructions of real-world scenes from multi-view 2D…

Computer Vision and Pattern Recognition · Computer Science 2026-03-31 Yuqiu Liu , Jialin Song , Marissa Ramirez de Chanlatte , Rochishnu Chowdhury , Rushil Paresh Desai , Wuyang Chen , Daniel Martin , Michael W. Mahoney

Although significant progress has been made in reconstructing sharp 3D scenes from motion-blurred images, a transition to real-world applications remains challenging. The primary obstacle stems from the severe blur which leads to…

Computer Vision and Pattern Recognition · Computer Science 2024-04-19 Jeongtaek Oh , Jaeyoung Chung , Dongwoo Lee , Kyoung Mu Lee

Rendering novel view images in dynamic scenes is a crucial yet challenging task. Current methods mainly utilize NeRF-based methods to represent the static scene and an additional time-variant MLP to model scene deformations, resulting in…

Computer Vision and Pattern Recognition · Computer Science 2024-06-07 Diwen Wan , Ruijie Lu , Gang Zeng

Implicit neural representation has paved the way for new approaches to dynamic scene reconstruction and rendering. Nonetheless, cutting-edge dynamic neural rendering methods rely heavily on these implicit representations, which frequently…

Computer Vision and Pattern Recognition · Computer Science 2023-11-22 Ziyi Yang , Xinyu Gao , Wen Zhou , Shaohui Jiao , Yuqing Zhang , Xiaogang Jin

3D Gaussian Splatting (3DGS) has revolutionized 3D scene reconstruction, which effectively balances rendering quality, efficiency, and speed. However, existing 3DGS approaches usually generate plausible outputs and face significant…

Graphics · Computer Science 2025-07-22 Beizhen Zhao , Yifan Zhou , Sicheng Yu , Zijian Wang , Hao Wang

The standard approach to densely reconstruct the motion in a volume of fluid is to inject high-contrast tracer particles and record their motion with multiple high-speed cameras. Almost all existing work processes the acquired multi-view…

Computer Vision and Pattern Recognition · Computer Science 2019-11-25 Katrin Lasinger , Christoph Vogel , Thomas Pock , Konrad Schindler

3D scene stylization extends the work of neural style transfer to 3D. A vital challenge in this problem is to maintain the uniformity of the stylized appearance across multiple views. A vast majority of the previous works achieve this by…

Computer Vision and Pattern Recognition · Computer Science 2024-09-09 Abhishek Saroha , Mariia Gladkova , Cecilia Curreli , Dominik Muhle , Tarun Yenamandra , Daniel Cremers

Gaussian splatting has become a popular representation for novel-view synthesis, exhibiting clear strengths in efficiency, photometric quality, and compositional edibility. Following its success, many works have extended Gaussians to 4D,…

Computer Vision and Pattern Recognition · Computer Science 2024-09-12 Colton Stearns , Adam Harley , Mikaela Uy , Florian Dubost , Federico Tombari , Gordon Wetzstein , Leonidas Guibas