SOTAVerified

Autonomous Vehicles

Autonomous vehicles is the task of making a vehicle that can guide itself 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: GSNet: Joint Vehicle Pose and Shape Reconstruction with Geometrical and Scene-aware Supervision )

Papers

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Showing 301–325 of 2605 papers

TitleStatusHype
Pylot: A Modular Platform for Exploring Latency-Accuracy Tradeoffs in Autonomous VehiclesCode1
DSLR: Dynamic to Static LiDAR Scan Reconstruction Using Adversarially Trained AutoencoderCode1
MTH-IDS: A Multi-Tiered Hybrid Intrusion Detection System for Internet of VehiclesCode1
M4Depth: Monocular depth estimation for autonomous vehicles in unseen environmentsCode1
Deep Multi-agent Reinforcement Learning for Highway On-Ramp Merging in Mixed TrafficCode1
Coupling Intent and Action for Pedestrian Crossing Behavior PredictionCode1
Investigating the Impact of Multi-LiDAR Placement on Object Detection for Autonomous DrivingCode1
Adversarial Example Detection for DNN Models: A Review and Experimental ComparisonCode1
Lane Graph Estimation for Scene Understanding in Urban DrivingCode1
Maneuver-Aware Pooling for Vehicle Trajectory PredictionCode1
MinkLoc++: Lidar and Monocular Image Fusion for Place RecognitionCode1
Raindrops on Windshield: Dataset and Lightweight Gradient-Based Detection AlgorithmCode1
Multimodal Object Detection via Probabilistic EnsemblingCode1
iCurb: Imitation Learning-based Detection of Road Curbs using Aerial Images for Autonomous DrivingCode1
Topo-boundary: A Benchmark Dataset on Topological Road-boundary Detection Using Aerial Images for Autonomous DrivingCode1
SIENet: Spatial Information Enhancement Network for 3D Object Detection from Point CloudCode1
SUTD-TrafficQA: A Question Answering Benchmark and an Efficient Network for Video Reasoning over Traffic EventsCode1
Fooling LiDAR Perception via Adversarial Trajectory PerturbationCode1
S-AT GCN: Spatial-Attention Graph Convolution Network based Feature Enhancement for 3D Object DetectionCode1
Understanding the Robustness of Skeleton-based Action Recognition under Adversarial AttackCode1
Split Computing and Early Exiting for Deep Learning Applications: Survey and Research ChallengesCode1
Sequential Place Learning: Heuristic-Free High-Performance Long-Term Place RecognitionCode1
DR-TANet: Dynamic Receptive Temporal Attention Network for Street Scene Change DetectionCode1
Categorical Depth Distribution Network for Monocular 3D Object DetectionCode1
Scalable Scene Flow from Point Clouds in the Real WorldCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1BAAMA3DP22.85—Unverified
2GSNetA3DP20.21—Unverified