6 papers
GenDet: Painting Colored Bounding Boxes on Images via Diffusion Model for Object Detection
Chen Min, Chengyang Li, Fanjie Kong +3
This paper presents GenDet, a novel framework that redefines object detection as an image generation task. In contrast to traditional approaches, GenDet adopts a pioneering approac…
A Vision-Language-Action Model with Visual Prompt for OFF-Road Autonomous Driving
Liangdong Zhang, Yiming Nie, Haoyang Li +6
Efficient trajectory planning in off-road terrains presents a formidable challenge for autonomous vehicles, often necessitating complex multi-step pipelines. However, traditional a…
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,…
PointSlice: Accurate and Efficient Slice-Based Representation for 3D Object Detection from Point Clouds
Liu Qifeng, Zhao Dawei, Dong Yabo +7
3D object detection from point clouds plays a critical role in autonomous driving. Currently, the primary methods for point cloud processing are voxel-based and pillar-based approa…
Voxel Densification for Serialized 3D Object Detection: Mitigating Sparsity via Pre-serialization Expansion
Qifeng Liu, Dawei Zhao, Yabo Dong +6
Recent advances in point cloud object detection have increasingly adopted Transformer-based and State Space Models (SSMs) to capture long-range dependencies. However, these seriali…
DriveWorld: 4D Pre-trained Scene Understanding via World Models for Autonomous Driving
Chen Min, Dawei Zhao, Liang Xiao +10
Vision-centric autonomous driving has recently raised wide attention due to its lower cost. Pre-training is essential for extracting a universal representation. However, current vi…