82 citations · 170 across the 20 of their papers we have counts for
16 papers · 1 filter
ReSim: Reliable World Simulation for Autonomous Driving
Jiazhi Yang, Kashyap Chitta, Shenyuan Gao +7
How can we reliably simulate future driving scenarios under a wide range of ego driving behaviors? Recent driving world models, developed exclusively on real-world driving data com…
Vista: A Generalizable Driving World Model with High Fidelity and Versatile Controllability
Shenyuan Gao, Jiazhi Yang, Li Chen +5
World models can foresee the outcomes of different actions, which is of paramount importance for autonomous driving. Nevertheless, existing driving world models still have limitati…
GenAD: Generalized Predictive Model for Autonomous Driving
Jiazhi Yang, Shenyuan Gao, Yihang Qiu +11
In this paper, we introduce the first large-scale video prediction model in the autonomous driving discipline. To eliminate the restriction of high-cost data collection and empower…
Visual Point Cloud Forecasting enables Scalable Autonomous Driving
Zetong Yang, Li Chen, Yanan Sun +1
In contrast to extensive studies on general vision, pre-training for scalable visual autonomous driving remains seldom explored. Visual autonomous driving applications require feat…
LaneSegNet: Map Learning with Lane Segment Perception for Autonomous Driving
Tianyu Li, Peijin Jia, Bangjun Wang +4
A map, as crucial information for downstream applications of an autonomous driving system, is usually represented in lanelines or centerlines. However, existing literature on map l…
Scene as Occupancy
Chonghao Sima, Wenwen Tong, Tai Wang +8
Human driver can easily describe the complex traffic scene by visual system. Such an ability of precise perception is essential for driver's planning. To achieve this, a geometry-a…
Think Twice before Driving: Towards Scalable Decoders for End-to-End Autonomous Driving
Xiaosong Jia, Penghao Wu, Li Chen +4
End-to-end autonomous driving has made impressive progress in recent years. Existing methods usually adopt the decoupled encoder-decoder paradigm, where the encoder extracts hidden…
OpenLane-V2: A Topology Reasoning Benchmark for Unified 3D HD Mapping
Huijie Wang, Tianyu Li, Yang Li +13
Accurately depicting the complex traffic scene is a vital component for autonomous vehicles to execute correct judgments. However, existing benchmarks tend to oversimplify the scen…
Graph-based Topology Reasoning for Driving Scenes
Tianyu Li, Li Chen, Huijie Wang +10
Understanding the road genome is essential to realize autonomous driving. This highly intelligent problem contains two aspects - the connection relationship of lanes, and the assig…
Policy Pre-training for Autonomous Driving via Self-supervised Geometric Modeling
Penghao Wu, Li Chen, Hongyang Li +3
Witnessing the impressive achievements of pre-training techniques on large-scale data in the field of computer vision and natural language processing, we wonder whether this idea c…
Planning-oriented Autonomous Driving
Yihan Hu, Jiazhi Yang, Li Chen +13
Modern autonomous driving system is characterized as modular tasks in sequential order, i.e., perception, prediction, and planning. In order to perform a wide diversity of tasks an…
Delving into the Devils of Bird's-eye-view Perception: A Review, Evaluation and Recipe
Hongyang Li, Chonghao Sima, Jifeng Dai +19
Learning powerful representations in bird's-eye-view (BEV) for perception tasks is trending and drawing extensive attention both from industry and academia. Conventional approaches…
ST-P3: End-to-end Vision-based Autonomous Driving via Spatial-Temporal Feature Learning
Shengchao Hu, Li Chen, Penghao Wu +3
Many existing autonomous driving paradigms involve a multi-stage discrete pipeline of tasks. To better predict the control signals and enhance user safety, an end-to-end approach t…
Level 2 Autonomous Driving on a Single Device: Diving into the Devils of Openpilot
Li Chen, Tutian Tang, Zhitian Cai +6
Equipped with a wide span of sensors, predominant autonomous driving solutions are becoming more modular-oriented for safe system design. Though these sensors have laid a solid fou…
Trajectory-guided Control Prediction for End-to-end Autonomous Driving: A Simple yet Strong Baseline
Penghao Wu, Xiaosong Jia, Li Chen +3
Current end-to-end autonomous driving methods either run a controller based on a planned trajectory or perform control prediction directly, which have spanned two separately studie…
PersFormer: 3D Lane Detection via Perspective Transformer and the OpenLane Benchmark
Li Chen, Chonghao Sima, Yang Li +8
Methods for 3D lane detection have been recently proposed to address the issue of inaccurate lane layouts in many autonomous driving scenarios (uphill/downhill, bump, etc.). Previo…