Autonomous Driving
1415 papers with code • 4 benchmarks • 66 datasets
Autonomous driving is the task of driving a vehicle without human conduction.
Many of the state-of-the-art results can be found at more general task pages such as 3D Object Detection and Semantic Segmentation.
(Image credit: Exploring the Limitations of Behavior Cloning for Autonomous Driving)
Benchmarks
These leaderboards are used to track progress in Autonomous Driving
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Libraries
Use these libraries to find Autonomous Driving models and implementationsDatasets
CARLA
Waymo Open Dataset
AirSim
Virtual KITTI
TORCS
IDD
INTERACTION Dataset
ApolloScape
SemanticPOSS
WoodScape
Latest papers
BACS: Background Aware Continual Semantic Segmentation
Besides the common problem of classical catastrophic forgetting in the continual learning setting, CSS suffers from the inherent ambiguity of the background, a phenomenon we refer to as the "background shift'', since pixels labeled as background could correspond to future classes (forward background shift) or previous classes (backward background shift).
VG4D: Vision-Language Model Goes 4D Video Recognition
By transferring the knowledge of the VLM to the 4D encoder and combining the VLM, our VG4D achieves improved recognition performance.
Sky-GVIO: an enhanced GNSS/INS/Vision navigation with FCN-based sky-segmentation in urban canyon
Building upon this, a novel NLOS detection and mitigation algorithm (named S-NDM) is extended to the tightly coupled Global Navigation Satellite Systems (GNSS), Inertial Measurement Units (IMU), and visual feature system which is called Sky-GVIO, with the aim of achieving continuous and accurate positioning in urban canyon environments.
KI-GAN: Knowledge-Informed Generative Adversarial Networks for Enhanced Multi-Vehicle Trajectory Forecasting at Signalized Intersections
Reliable prediction of vehicle trajectories at signalized intersections is crucial to urban traffic management and autonomous driving systems.
VRS-NeRF: Visual Relocalization with Sparse Neural Radiance Field
However, in spite of high efficiency, APRs and SCRs have limited accuracy especially in large-scale outdoor scenes; HMs are accurate but need to store a large number of 2D descriptors for matching, resulting in poor efficiency.
Intention-Aware Control Based on Belief-Space Specifications and Stochastic Expansion
This paper develops a correct-by-design controller for an autonomous vehicle interacting with opponent vehicles with unknown intentions.
SEVD: Synthetic Event-based Vision Dataset for Ego and Fixed Traffic Perception
In response to this gap, we present SEVD, a first-of-its-kind multi-view ego, and fixed perception synthetic event-based dataset using multiple dynamic vision sensors within the CARLA simulator.
WROOM: An Autonomous Driving Approach for Off-Road Navigation
Off-road navigation is a challenging problem both at the planning level to get a smooth trajectory and at the control level to avoid flipping over, hitting obstacles, or getting stuck at a rough patch.
PASA: Attack Agnostic Unsupervised Adversarial Detection using Prediction & Attribution Sensitivity Analysis
dipkamal/pasa
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However, we observe that both model predictions and feature attributions for input samples are sensitive to noise.
Homography Guided Temporal Fusion for Road Line and Marking Segmentation
Reliable segmentation of road lines and markings is critical to autonomous driving.
