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Found 8 papers, 7 papers with code
Can Vehicle Motion Planning Generalize to Realistic Long-tail Scenarios?
We assess existing state-of-the-art planners on our benchmark and show that neither rule-based nor learning-based planners can safely navigate the interPlan scenarios.
DriveLM: Driving with Graph Visual Question Answering
The experiments demonstrate that Graph VQA provides a simple, principled framework for reasoning about a driving scene, and DriveLM-Data provides a challenging benchmark for this task.
On Offline Evaluation of 3D Object Detection for Autonomous Driving
Prior work in 3D object detection evaluates models using offline metrics like average precision since closed-loop online evaluation on the downstream driving task is costly.
PlanT: Explainable Planning Transformers via Object-Level Representations
Planning an optimal route in a complex environment requires efficient reasoning about the surrounding scene.
Ranked #6 on
CARLA longest6
on CARLA
TransFuser: Imitation with Transformer-Based Sensor Fusion for Autonomous Driving
At the time of submission, TransFuser outperforms all prior work on the CARLA leaderboard in terms of driving score by a large margin.
Ranked #6 on
Autonomous Driving
on CARLA Leaderboard
KING: Generating Safety-Critical Driving Scenarios for Robust Imitation via Kinematics Gradients
Simulators offer the possibility of safe, low-cost development of self-driving systems.
Sign Segmentation with Changepoint-Modulated Pseudo-Labelling
The objective of this work is to find temporal boundaries between signs in continuous sign language.
Sign language segmentation with temporal convolutional networks
The objective of this work is to determine the location of temporal boundaries between signs in continuous sign language videos.
