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Novel view synthesis for underwater scene reconstruction presents unique challenges due to complex light-media interactions. Optical scattering and absorption in water body bring inhomogeneous medium attenuation interference that disrupts…

Computer Vision and Pattern Recognition · Computer Science 2026-05-14 Jieyu Yuan , Yujun Li , Yuanlin Zhang , Chunle Guo , Xiongxin Tang , Ruixing Wang , Chongyi Li

Reconstructing Dynamic 3D Gaussian Splatting (3DGS) from low-framerate RGB videos is challenging. This is because large inter-frame motions will increase the uncertainty of the solution space. For example, one pixel in the first frame might…

Computer Vision and Pattern Recognition · Computer Science 2025-12-12 Junhao He , Jiaxu Wang , Jia Li , Mingyuan Sun , Qiang Zhang , Jiahang Cao , Ziyi Zhang , Yi Gu , Jingkai Sun , Renjing Xu

In recent years, 3D Gaussian splatting has emerged as a powerful technique for 3D reconstruction and generation, known for its fast and high-quality rendering capabilities. To address these shortcomings, this paper introduces a novel…

Computer Vision and Pattern Recognition · Computer Science 2024-07-17 Xianglong He , Junyi Chen , Sida Peng , Di Huang , Yangguang Li , Xiaoshui Huang , Chun Yuan , Wanli Ouyang , Tong He

3D Gaussian Splatting (3DGS) has recently emerged as a state-of-the-art 3D reconstruction and rendering technique due to its high-quality results and fast training and rendering time. However, pixels covered by the same Gaussian are always…

Computer Vision and Pattern Recognition · Computer Science 2025-10-07 Brian Chao , Hung-Yu Tseng , Lorenzo Porzi , Chen Gao , Tuotuo Li , Qinbo Li , Ayush Saraf , Jia-Bin Huang , Johannes Kopf , Gordon Wetzstein , Changil Kim

3D Gaussian Splatting (3DGS) has witnessed exponential adoption across diverse applications, driving a critical need for semantic-aware 3D Gaussian representations to enable scene understanding and editing tasks. Existing approaches…

Computer Vision and Pattern Recognition · Computer Science 2025-08-05 Zhaonan Wang , Manyi Li , Changhe Tu

Shape and geometric patterns are essential in defining stylistic identity. However, current 3D style transfer methods predominantly focus on transferring colors and textures, often overlooking geometric aspects. In this paper, we introduce…

Computer Vision and Pattern Recognition · Computer Science 2024-04-09 Hyunyoung Jung , Seonghyeon Nam , Nikolaos Sarafianos , Sungjoo Yoo , Alexander Sorkine-Hornung , Rakesh Ranjan

Sand painting is a process-driven art where visual appearance emerges from granular accumulation. Given a single image, reconstructing a plausible sand painting process requires modeling coherent stroke structures and material-dependent…

Graphics · Computer Science 2026-05-01 Yilin Wang , Haojie Huang , Chen Li , Yang Li , Changbo Wang , Chenhui Li

Accurate 3D reconstruction in degraded imaging conditions remains a key challenge in photogrammetry and neural rendering. In underwater environments, spatially varying visibility caused by scattering, attenuation, and sparse observations…

Computer Vision and Pattern Recognition · Computer Science 2026-04-23 Zhuodong Jiang , Haoran Wang , Guoxi Huang , Brett Seymour , Nantheera Anantrasirichai

The problem of 3D reconstruction from posed images is undergoing a fundamental transformation, driven by continuous advances in 3D Gaussian Splatting (3DGS). By modeling scenes explicitly as collections of 3D Gaussians, 3DGS enables…

Computer Vision and Pattern Recognition · Computer Science 2026-03-02 Vitor Pereira Matias , Daniel Perazzo , Vinicius Silva , Alberto Raposo , Luiz Velho , Afonso Paiva , Tiago Novello

Recent advances in 3D Gaussian Splatting (3DGS) have enabled impressive real-time photorealistic rendering. However, conventional training pipelines inherently assume full multi-view consistency among input images, which makes them…

Computer Vision and Pattern Recognition · Computer Science 2026-04-17 Kangmin Seo , MinKyu Lee , Tae-Young Kim , ByeongCheol Lee , JoonSeoung An , Jae-Pil Heo

3D Gaussian Splatting has recently gained traction for its efficient training and real-time rendering. While its vanilla representation is mainly designed for view synthesis, recent works extended it to scene understanding with language…

Computer Vision and Pattern Recognition · Computer Science 2026-01-21 Siyun Liang , Sen Wang , Kunyi Li , Michael Niemeyer , Stefano Gasperini , Hendrik P. A. Lensch , Nassir Navab , Federico Tombari

The transformative potential of 3D content creation has been progressively unlocked through advancements in generative models. Recently, intuitive drag editing with geometric changes has attracted significant attention in 2D editing yet…

Computer Vision and Pattern Recognition · Computer Science 2026-01-14 Jiahua Dong , Yu-Xiong Wang

Feed-forward surround-view autonomous driving scene reconstruction offers fast, generalizable inference ability, which faces the core challenge of ensuring generalization while elevating novel view quality. Due to the surround-view with…

Computer Vision and Pattern Recognition · Computer Science 2025-10-23 Junhong Lin , Kangli Wang , Shunzhou Wang , Songlin Fan , Ge Li , Wei Gao

Neural scene representations, such as 3D Gaussian Splatting (3DGS), have enabled high-quality neural rendering; however, their large storage and transmission costs hinder deployment in resource-constrained environments. Existing compression…

Computer Vision and Pattern Recognition · Computer Science 2026-03-10 Jiaqi Chen , Xinhao Ji , Yuanyuan Gao , Hao Li , Yuning Gong , Yifei Liu , Dan Xu , Zhihang Zhong , Dingwen Zhang , Xiao Sun

We propose VideoRFSplat, a direct text-to-3D model leveraging a video generation model to generate realistic 3D Gaussian Splatting (3DGS) for unbounded real-world scenes. To generate diverse camera poses and unbounded spatial extent of…

Computer Vision and Pattern Recognition · Computer Science 2025-03-21 Hyojun Go , Byeongjun Park , Hyelin Nam , Byung-Hoon Kim , Hyungjin Chung , Changick Kim

Radiance field methods, such as Neural Radiance Field or 3D Gaussian Splatting, have emerged as seminal 3D representations for synthesizing realistic novel views. For practical applications, there is ongoing research on flexible scene…

Computer Vision and Pattern Recognition · Computer Science 2025-07-14 Ji Hyun Seo , Byounhyun Yoo , Gerard Jounghyun Kim

Reconstructing 3D assets from images, known as inverse rendering (IR), remains a challenging task due to its ill-posed nature. 3D Gaussian Splatting (3DGS) has demonstrated impressive capabilities for novel view synthesis (NVS) tasks.…

Computer Vision and Pattern Recognition · Computer Science 2025-04-10 Hanxiao Sun , YuPeng Gao , Jin Xie , Jian Yang , Beibei Wang

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

In this paper, we propose an end-to-end transcoding pipeline, to create 3D Gaussian splatting (3DGS) models from existing 3D plenoptic point cloud or mesh models, when the original multi-view images of the captured 3D object or scene are…

Image and Video Processing · Electrical Eng. & Systems 2026-05-21 Maja Krivokuća , Riad Bendouro , Neus Sabater

We introduce Crowd-Sourced Splatting (CSS), a novel 3D Gaussian Splatting (3DGS) pipeline designed to overcome the challenges of pose-free scene reconstruction using crowd-sourced imagery. The dream of reconstructing historically…

Computer Vision and Pattern Recognition · Computer Science 2024-09-16 Runze Chen , Mingyu Xiao , Haiyong Luo , Fang Zhao , Fan Wu , Hao Xiong , Qi Liu , Meng Song