1 citations · 1 across the 4 of their papers we have counts for
9 papers
DinoLink: A Token-Centric Representation Compression Framework for Bandwidth-Constrained Collaborative V2X Perception
Tianle Zhu, Haohua Que, Handong Yao +2
High-precision remote perception is often hindered by the severe bandwidth constraints of Vehicle-to-Everything (V2X) networks. We propose \textit{DinoLink}, a token-centric compre…
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.…
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…
CABLE: Cloud-Assisted Bandwidth-efficient LMM-based Encoding for V2X Systems
Haohua Que, Zhipeng Bao, Qianyi Wu +1
Cloud-hosted large multimodal models (LMMs) can provide strong open-vocabulary perception for Vehicle-to-Everything systems, but naively transmitting full-resolution frames from ed…
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…