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Yunlong Ran

7 accepted papers

2026

DiffPBR: Point-Based Rendering via Spatial-Aware Residual Diffusion

ICLR 2026poster

Neural radiance fields and 3D Gaussian splatting (3DGS) have significantly advanced 3D reconstruction and novel view synthesis (NVS). Yet, achieving high-fidelity and view-consistent renderings directly from point clouds---without costly per-scene optimization---remains a core challenge. In this wor…

Cited by 0SourceScholar
2026

G$^2$TAM: Geometry Grounded Track Anything Model

ICML 2026poster

Human spatial understanding arises from jointly perceiving geometry and semantics, enabling consistent object identification and localization across viewpoints and time. Current video segmentation models depend on explicit object appearance memory banks for instance tracking, yet they remain vulnera…

Cited by 0SourceScholar
2026

G$^2$VLM: Geometry Grounded Vision Language Model with Unified 3D Reconstruction and Spatial Reasoning

CVPR 2026

Vision-Language Models (VLMs) still lack robustness in spatial intelligence, demonstrating poor performance on spatial understanding and reasoning tasks. We attribute this gap to the absence of a visual geometry learning process capable of reconstructing 3D space from 2D images. We present G^2VLM, a

Cited by 0SourcecodeScholar
2024

Autonomous Implicit Indoor Scene Reconstruction with Frontier Exploration

ICRA 2024poster

Implicit neural representations have demonstrated significant promise for 3D scene reconstruction. Recent works have extended their applications to autonomous implicit reconstruction through the Next Best View (NBV) based method. However, the NBV method cannot guarantee complete scene coverage and o…

Cited by 3SourceScholar
2023

Efficient View Path Planning for Autonomous Implicit Reconstruction

ICRA 2023poster

Implicit neural representations have shown promising potential for 3D scene reconstruction. Recent work applies it to autonomous 3D reconstruction by learning information gain for view path planning. Effective as it is, the computation of the information gain is expensive, and compared with that usi…

Cited by 20SourceScholar
2023

NeurAR: Neural Uncertainty for Autonomous 3D Reconstruction With Implicit Neural Representations

RA-L 2023

Implicit neural representations have shown compelling results in offline 3D reconstruction and also recently demonstrated the potential for online SLAM systems. However, applying them to autonomous 3D reconstruction, where a robot is required to explore a scene and plan a view path for the reconstru

Cited by 91SourceScholar
2023

Seal-3D: Interactive Pixel-Level Editing for Neural Radiance Fields

ICCV 2023poster

With the popularity of implicit neural representations, or neural radiance fields (NeRF), there is a pressing need for editing methods to interact with the implicit 3D models for tasks like post-processing reconstructed scenes and 3D content creation. While previous works have explored NeRF editing…

Cited by 18PDFcodeScholar