6 papers
CoGeo-GS: Concept-Driven and Geometry-Aware Multi-Object Removal in 3D Scenes
Yuanxiang Ni, Xianliang Huang, Chenhang Ma +4
Multi-object removal in 3D scenes is challenging due to severe occlusions, semantic entanglement, and the difficulty of maintaining geometric and multi-view consistency. Existing 3…
Semantic-Guided Progressive Object Removal with Gaussian Splatting
Xianliang Huang, Chen Xiao, Yuanxiang Ni +5
Removing unwanted objects from reconstructed 3D scenes is an important task in computer vision, supporting applications in AR/VR, robotics, and digital content creation. Existing m…
ACEsplat: Accelerated 3D Gaussian Scene Regression via RGB and Poses Only
Mingkai Liu, Haohua Que, Dikai Fan +7
Per-scene 3D Gaussian Splatting (3DGS) enables high-fidelity rendering, but practical robotic and AR scene capture pipelines often depend on external geometric initialization (e.g.…
IntPro: A Proxy Agent for Context-Aware Intent Understanding via Retrieval-conditioned Inference
Guanming Liu, Meng Wu, Peng Zhang +8
Large language models (LLMs) have become integral to modern Human-AI collaboration workflows, where accurately understanding user intent serves as a crucial step for generating sat…
Hybrid Cross-Device Localization via Neural Metric Learning and Feature Fusion
Meixia Lin, Mingkai Liu, Shuxue Peng +5
We present a hybrid cross-device localization pipeline developed for the CroCoDL 2025 Challenge. Our approach integrates a shared retrieval encoder and two complementary localizati…
MACE: Mixture-of-Experts Accelerated Coordinate Encoding for Large-Scale Scene Localization and Rendering
Mingkai Liu, Dikai Fan, Haohua Que +10
Efficient localization and high-quality rendering in large-scale scenes remain a significant challenge due to the computational cost involved. While Scene Coordinate Regression (SC…