2 citations · 5 across the 15 of their papers we have counts for
11 papers · 1 filter
Evidence-gated multimodal parsing and vectorization of architectural floor plans
Hongxuan Chen, Wenda Wang, Jiachen Lu +5
Architectural floor plans remain a high-friction barrier to archive digitization and early design-model preparation because heterogeneous graphics encode spatial semantics and edit…
RS2AD-LiDAR: End-to-End Autonomous Driving LiDAR Data Generation from Roadside Sensor Observations
Runyi Huang, Ni Ding, Ruidan Xing +3
End-to-end autonomous driving solutions, which directly process multimodal sensory data and output fine-grained control commands, have gradually become a mainstream direction with…
ArchSIBench: Benchmarking the Architectural Spatial Intelligence of Vision-Language Models
Qirui Shen, Wenda Wang, Jiachen Lu +5
Architectural spatial intelligence, the ability to recognize and infer architectural space, is fundamental to tasks such as robot navigation, embodied interaction, and 3D scene und…
Sketch2MinSurf: Vision-Language Guided Generation of Editable Minimal Surfaces from Hand-Drawn Sketches
Wenda Wang, Anqi Liu, Junqi Yang +4
Converting hand-drawn sketches into structured 3D geometries remains challenging due to the difficulty of representing non-Euclidean surfaces and maintaining topological consistenc…
V2X-DGPE: Addressing Domain Gaps and Pose Errors for Robust Collaborative 3D Object Detection
Sichao Wang, Ming Yuan, Chuang Zhang +3
In V2X collaborative perception, the domain gaps between heterogeneous nodes pose a significant challenge for effective information fusion. Pose errors arising from latency and GPS…
Unveiling the Black Box: Independent Functional Module Evaluation for Bird's-Eye-View Perception Model
Ludan Zhang, Xiaokang Ding, Yuqi Dai +2
End-to-end models are emerging as the mainstream in autonomous driving perception. However, the inability to meticulously deconstruct their internal mechanisms results in diminishe…
Vision-Driven 2D Supervised Fine-Tuning Framework for Bird's Eye View Perception
Lei He, Qiaoyi Wang, Honglin Sun +5
Visual bird's eye view (BEV) perception, due to its excellent perceptual capabilities, is progressively replacing costly LiDAR-based perception systems, especially in the realm of…
GS-Net: Heterogeneous Vehicle Data Reuse via Generalizable Plug-and-Play 3DGS Module
Yichen Zhang, Zihan Wang, Jiali Han +5
End-to-end autonomous driving is increasingly data-driven, yet data reuse across vehicles remains limited. Each new vehicle often requires additional data collection and retraining…
Hierarchical and Decoupled BEV Perception Learning Framework for Autonomous Driving
Yuqi Dai, Jian Sun, Shengbo Eben Li +4
Perception is essential for autonomous driving system. Recent approaches based on Bird's-eye-view (BEV) and deep learning have made significant progress. However, there exists chal…
OE-BevSeg: An Object Informed and Environment Aware Multimodal Framework for Bird's-eye-view Vehicle Semantic Segmentation
Jian Sun, Yuqi Dai, Chi-Man Vong +5
Bird's-eye-view (BEV) semantic segmentation is becoming crucial in autonomous driving systems. It realizes ego-vehicle surrounding environment perception by projecting 2D multi-vie…
Neural Radiance Field in Autonomous Driving: A Survey
Lei He, Leheng Li, Wenchao Sun +5
Neural Radiance Field (NeRF) has garnered significant attention from both academia and industry due to its intrinsic advantages, particularly its implicit representation and novel…