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Injecting semantics into 3D Gaussian Splatting (3DGS) has recently garnered significant attention. While current approaches typically distill 3D semantic features from 2D foundational models (e.g., CLIP and SAM) to facilitate novel view…

计算机视觉与模式识别 · 计算机科学 2025-05-20 Wenbo Zhang , Lu Zhang , Ping Hu , Liqian Ma , Yunzhi Zhuge , Huchuan Lu

Capturing 4D spatiotemporal surroundings is crucial for the safe and reliable operation of robots in dynamic environments. However, most existing methods address only one side of the problem: they either provide coarse geometric tracking…

计算机视觉与模式识别 · 计算机科学 2026-02-27 Maximilian Luz , Rohit Mohan , Thomas Nürnberg , Yakov Miron , Daniele Cattaneo , Abhinav Valada

Accurate 3D reconstruction of dynamic surgical scenes from endoscopic video is essential for robotic-assisted surgery. While recent 3D Gaussian Splatting methods have shown promise in achieving high-quality reconstructions with fast…

计算机视觉与模式识别 · 计算机科学 2024-10-15 Jialei Chen , Xin Zhang , Mobarakol Islam , Francisco Vasconcelos , Danail Stoyanov , Daniel S. Elson , Baoru Huang

Training neural networks for tasks such as 3D point cloud semantic segmentation demands extensive datasets, yet obtaining and annotating real-world point clouds is costly and labor-intensive. This work aims to introduce a novel pipeline for…

Recently, the 3D Gaussian Splatting (3D-GS) method has achieved great success in novel view synthesis, providing real-time rendering while ensuring high-quality rendering results. However, this method faces challenges in modeling specular…

计算机视觉与模式识别 · 计算机科学 2024-09-11 Zhiru Wang , Shiyun Xie , Chengwei Pan , Guoping Wang

3D Gaussian Splatting has emerged as an alternative 3D representation for novel view synthesis, benefiting from its high-quality rendering results and real-time rendering speed. However, the 3D Gaussians learned by 3D-GS have ambiguous…

计算机视觉与模式识别 · 计算机科学 2025-01-22 Xu Hu , Yuxi Wang , Lue Fan , Chuanchen Luo , Junsong Fan , Zhen Lei , Qing Li , Junran Peng , Zhaoxiang Zhang

Open-set semantic mapping requires (i) determining the correct granularity to represent the scene (e.g., how should objects be defined), and (ii) fusing semantic knowledge across multiple 2D observations into an overall 3D reconstruction…

计算机视觉与模式识别 · 计算机科学 2025-03-11 Dominic Maggio , Luca Carlone

Radiance fields have demonstrated impressive performance in synthesizing lifelike 3D talking heads. However, due to the difficulty in fitting steep appearance changes, the prevailing paradigm that presents facial motions by directly…

计算机视觉与模式识别 · 计算机科学 2024-07-08 Jiahe Li , Jiawei Zhang , Xiao Bai , Jin Zheng , Xin Ning , Jun Zhou , Lin Gu

In recent years, modern techniques in deep learning and large-scale datasets have led to impressive progress in 3D instance segmentation, grasp pose estimation, and robotics. This allows for accurate detection directly in 3D scenes, object-…

机器人学 · 计算机科学 2024-04-22 Oliver Lemke , Zuria Bauer , René Zurbrügg , Marc Pollefeys , Francis Engelmann , Hermann Blum

3D Visual Grounding (3DVG) aims to locate objects in 3D scenes based on text prompts, which is essential for applications such as robotics. However, existing 3DVG methods encounter two main challenges: first, they struggle to handle the…

计算机视觉与模式识别 · 计算机科学 2026-01-27 Liwei Liao , Xufeng Li , Xiaoyun Zheng , Boning Liu , Feng Gao , Ronggang Wang

We propose a novel 3D deepfake generation framework based on 3D Gaussian Splatting that enables realistic, identity-preserving face swapping and reenactment in a fully controllable 3D space. Compared to conventional 2D deepfake approaches…

计算机视觉与模式识别 · 计算机科学 2025-09-16 Wending Liu , Siyun Liang , Huy H. Nguyen , Isao Echizen

The emergence of 3D Gaussian Splatting (3DGS) has greatly accelerated the rendering speed of novel view synthesis. Unlike neural implicit representations like Neural Radiance Fields (NeRF) that represent a 3D scene with position and…

计算机视觉与模式识别 · 计算机科学 2024-04-16 Tong Wu , Yu-Jie Yuan , Ling-Xiao Zhang , Jie Yang , Yan-Pei Cao , Ling-Qi Yan , Lin Gao

In this paper, we propose a RGB-D SLAM system that reconstructs a language-aligned dense feature field while sustaining low-latency tracking and mapping. First, we introduce a Top-K Rendering pipeline, a high-throughput and…

机器人学 · 计算机科学 2026-02-10 Seongbo Ha , Sibaek Lee , Kyungsu Kang , Joonyeol Choi , Seungjun Tak , Hyeonwoo Yu

Object-level 3D reconstruction play important roles across domains such as cultural heritage digitization, industrial manufacturing, and virtual reality. However, existing Gaussian Splatting-based approaches generally rely on full-scene…

计算机视觉与模式识别 · 计算机科学 2026-03-17 Shuai Guo , Ao Guo , Junchao Zhao , Qi Chen , Yuxiang Qi , Zechuan Li , Dong Chen , Tianjia Shao , Mingliang Xu

3D Gaussian Splatting offers expressive scene reconstruction, modeling a broad range of visual, geometric, and semantic information. However, efficient real-time map reconstruction with data streamed from multiple robots and devices remains…

机器人学 · 计算机科学 2025-06-04 Javier Yu , Timothy Chen , Mac Schwager

3D Gaussian splatting (3DGS) is an innovative rendering technique that surpasses the neural radiance field (NeRF) in both rendering speed and visual quality by leveraging an explicit 3D scene representation. Existing 3DGS approaches require…

计算机视觉与模式识别 · 计算机科学 2025-06-13 Lintao Xiang , Hongpei Zheng , Yating Huang , Qijun Yang , Hujun Yin

We present the first unified framework for rate-distortion-optimized compression and segmentation of 3D Gaussian Splatting (3DGS). While 3DGS has proven effective for both real-time rendering and semantic scene understanding, prior works…

计算机视觉与模式识别 · 计算机科学 2026-01-21 Yu-Jen Tseng , Chia-Hao Kao , Jing-Zhong Chen , Alessandro Gnutti , Shao-Yuan Lo , Yen-Yu Lin , Wen-Hsiao Peng

Reconstructing high-fidelity underwater scenes remains a challenging task due to light absorption, scattering, and limited visibility inherent in aquatic environments. This paper presents an enhanced Gaussian Splatting-based framework that…

计算机视觉与模式识别 · 计算机科学 2025-09-03 Zhuodong Jiang , Haoran Wang , Guoxi Huang , Brett Seymour , Nantheera Anantrasirichai

We propose a method to enhance 3D Gaussian Splatting (3DGS)~\cite{Kerbl2023}, addressing challenges in initialization, optimization, and density control. Gaussian Splatting is an alternative for rendering realistic images while supporting…

计算机视觉与模式识别 · 计算机科学 2025-07-02 Xingjun Wang , Lianlei Shan

3D Gaussian Splatting (3DGS) has emerged as a powerful and efficient 3D representation for novel view synthesis. This paper extends 3DGS capabilities to inpainting, where masked objects in a scene are replaced with new contents that blend…

计算机视觉与模式识别 · 计算机科学 2025-04-28 Mingxuan Cui , Qing Guo , Yuyi Wang , Hongkai Yu , Di Lin , Qin Zou , Ming-Ming Cheng , Xi Li