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Found 7 papers, 5 papers with code
DriveMLM: Aligning Multi-Modal Large Language Models with Behavioral Planning States for Autonomous Driving
In this work, we delve into the potential of large language models (LLMs) in autonomous driving (AD).
Think Twice before Driving: Towards Scalable Decoders for End-to-End Autonomous Driving
End-to-end autonomous driving has made impressive progress in recent years.
Ranked #4 on
CARLA longest6
on CARLA
3D Data Augmentation for Driving Scenes on Camera
The proposed data augmentation approach contributes to a gain of 1. 7% and 1. 4% in terms of detection accuracy, on Waymo and nuScences respectively.
Delving into the Devils of Bird's-eye-view Perception: A Review, Evaluation and Recipe
As sensor configurations get more complex, integrating multi-source information from different sensors and representing features in a unified view come of vital importance.
General Incremental Learning with Domain-aware Categorical Representations
Continual learning is an important problem for achieving human-level intelligence in real-world applications as an agent must continuously accumulate knowledge in response to streaming data/tasks.
An EM Framework for Online Incremental Learning of Semantic Segmentation
Incremental learning of semantic segmentation has emerged as a promising strategy for visual scene interpretation in the open- world setting.
DER: Dynamically Expandable Representation for Class Incremental Learning
We address the problem of class incremental learning, which is a core step towards achieving adaptive vision intelligence.
