View-Dependent 3DGS

3DGS: 3D Gaussian Splatting

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8 papers1 paper in the last four weeks, against 1 the four weeks before. 0.0% of all new papers.

Remote Sensing Sparse-View 3D Gaussian Splatting via Depth Image-Based Rendering
Sep 28, 2026Jiaming Kang, Zhengxia Zou, Zhenwei Shi3D Gaussian Splatting 3D Reconstruction
Beihang University
GSPotential: Camera Potential Field for Sparse-View 3D Gaussian Splatting
Aug 29, 2026Zeyuan An, Yanghang Xiao, Zhiying Leng +2View-Dependent 3DGS 3D Gaussian Splatting
State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, Beijing, China · School of Computer Science and Engineering, Beihang University, Beijing, China · Zhongguancun Laboratory, Beijing, China
UniqueSplat: View-conditioned 3D Gaussian Splatting for Generalizable 3D Reconstruction
Aug 3, 2026Haixu Song, Xiaoke Yang, Shengjun Zhang +23D Gaussian Splatting Novel View Synthesis
Tsinghua University, China
Improving Sparse-View 3DGS Generalization via Flat Minima Optimization
Jul 1, 2026Kangmin Seo, Sangeek Hyun, MinKyu Lee +13D Gaussian Splatting Novel View Synthesis
Sungkyunkwan University, South Korea
TWINGS: Thin Plate Splines Warp-aligned Initialization for Sparse-View Gaussian Splatting
May 21, 2026Hyeseong Kim, Geonhui Son, Deukhee Lee +13D Gaussian Splatting Novel View Synthesis
Yonsei University · Korea Institute of Science and Technology
ViewSplat: View-Adaptive 3D Gaussian Splatting for Feed-Forward Synthesis
Mar 26, 2026Moonyeon Jeong, Seunggi Min, Suhyeon Lee +13D Gaussian Splatting Novel View Synthesis
University of Seoul · Korea Electronics Technology Institute
Pose-Free Omnidirectional Gaussian Splatting for 360-Degree Videos with Consistent Depth Priors
Mar 24, 2026Chuanqing Zhuang, Xin Lu, Zehui Deng +4View-Dependent 3DGS 3D Gaussian Splatting
School of Artificial Intelligence, University of Chinese Academy of Sciences · Chongqing University · Air Force Engineering University
HeroGS: Hierarchical Guidance for Robust 3D Gaussian Splatting under Sparse Views
Mar 1, 2026Jiashu Li, Xumeng Han, Zhaoyang Wei +5View-Dependent 3DGS 3D Gaussian Splatting
University of the Chinese Academy of Sciences

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Remote Sensing Sparse-View 3D Gaussian Splatting via Depth Image-Based Rendering

Jiaming Kang, Zhengxia Zou, Zhenwei Shi

Beihang University

3D Gaussian Splatting 3D Reconstruction Novel View Synthesis Sparse-View 3D Reconstruction View-Dependent 3DGS

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Remote sensing novel view synthesis under sparse observations remains challenging due to insufficient geometric constraints and limited cross-view supervision. Existing Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3DGS) methods are prone to overfitting and face challenges of depth ambiguities, missing cross-view information, and insufficient constraints in under-observed regions. To address these challenges, we propose DIBR-GS, a neural Gaussian Splatting framework that exploits Depth Image-Based Rendering (DIBR) to generate pseudo views for cross-view consistency supervision. Specifically, reliable geometric initialization is constructed by aligning monocular depth priors with sparse SfM reconstruction, and cross-view appearance priors are incorporated into neural Gaussian representations to enhance appearance modeling under sparse observations. Furthermore, we introduce a progressive DIBR-based pseudo-view supervision strategy to provide additional geometric and appearance constraints, enabling more complete reconstruction of weakly observed regions. In addition, a height-constrained anchor growth strategy is designed to suppress unreasonable Gaussian expansion. Experiments demonstrate that the proposed method achieves superior performance over existing approaches when training with only 3 input views. Compared with the previous best-performing method, it improves PSNR by 6.83 dB, with relative gains of 14% in SSIM and 60% in LPIPS, while maintaining competitive computational efficiency. Our code is available at https://github.com/kanehub/DIBR-GS