1 citations · 1 across the 4 of their papers we have counts for
7 papers
Towards All-Day Perception for Off-Road Driving: A Large-Scale Multispectral Dataset and Comprehensive Benchmark
Shuo Wang, Jilin Mei, Wenfei Guan +4
Off-road nighttime autonomous driving suffers from unreliable visible-light perception, making infrared modality crucial for accurate freespace detection. However, progress remains…
SSI-DM: Singularity Skipping Inversion of Diffusion Models
Chen Min, Enze Jiang, Jishen Peng +1
Inverting real images into the noise space is essential for editing tasks using diffusion models, yet existing methods produce non-Gaussian noise with poor editability due to the i…
OT-Drive: Out-of-Distribution Off-Road Traversable Area Segmentation via Optimal Transport
Zhihua Zhao, Guoqiang Li, Chen Min +1
Reliable traversable area segmentation in unstructured environments is critical for planning and decision-making in autonomous driving. However, existing data-driven approaches oft…
Beyond Endpoints: Path-Centric Reasoning for Vectorized Off-Road Network Extraction
Wenfei Guan, Jilin Mei, Tong Shen +4
Deep learning has advanced vectorized road extraction in urban settings, yet off-road environments remain underexplored and challenging. A significant domain gap causes advanced mo…
Advancing Off-Road Autonomous Driving: The Large-Scale ORAD-3D Dataset and Comprehensive Benchmarks
Chen Min, Jilin Mei, Heng Zhai +12
A major bottleneck in off-road autonomous driving research lies in the scarcity of large-scale, high-quality datasets and benchmarks. To bridge this gap, we present ORAD-3D, which,…
CORENet: Cross-Modal 4D Radar Denoising Network with LiDAR Supervision for Autonomous Driving
Fuyang Liu, Jilin Mei, Fangyuan Mao +3
4D radar-based object detection has garnered great attention for its robustness in adverse weather conditions and capacity to deliver rich spatial information across diverse drivin…