1 citations · 1 across the 9 of their papers we have counts for
9 papers
Think Locally, Refine Globally for Memory-Efficient 3D Reconstruction
Jingke Zhou, Chenhang Ma, Zhizhou Zhong +6
We propose LoG-VGGT, a memory-efficient framework for long-sequence 3D reconstruction that balances local temporal modeling with global camera consistency. Instead of relying on fu…
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…
SPACE: Swarm Pheromone Fields for Adaptive Collision-Aware Exploration
Haohua Que, Haojia Gao, Mingkai Liu +3
Massive robot swarms can explore unknown environments quickly, but adding robots eventually stops helping. Doorways and dense traffic create congestion, increasing inter-robot cont…
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.…
MotiMem: Motion-Aware Approximate Memory for Energy-Efficient Neural Perception in Autonomous Vehicles
Haohua Que, Mingkai Liu, Jiayue Xie +5
High-resolution sensors are critical for robust autonomous perception but impose a severe memory wall on battery-constrained electric vehicles. In these systems, data movement ener…
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…
Mapping at First Sense: A Lightweight Neural Network-Based Indoor Structures Prediction Method for Robot Autonomous Exploration
Haojia Gao, Haohua Que, Kunrong Li +7
Autonomous exploration in unknown environments is a critical challenge in robotics, particularly for applications such as indoor navigation, search and rescue, and service robotics…
SenseExpo: Spatial Exploration and Navigation via Scene Estimation from Expeditious Predictive Operators
Haojia Gao, Haohua Que, Mingkai Liu +9
We present \textbf{SenseExpo}, a lightweight single-robot exploration framework that integrates a compact map prediction network into a frontier-based strategy. SenseExpo addresses…