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 521–530 of 2605 papers

TitleStatusHype
Dynamically Modulating Visual Place Recognition Sequence Length For Minimum Acceptable Performance Scenarios—0
Deep Reinforcement Learning for Adverse Garage Scenario Generation—0
SeFlow: A Self-Supervised Scene Flow Method in Autonomous DrivingCode2
CSFNet: A Cosine Similarity Fusion Network for Real-Time RGB-X Semantic Segmentation of Driving ScenesCode1
Benchmarks for Reinforcement Learning with Biased Offline Data and Imperfect Simulators—0
Cooperative Advisory Residual Policies for Congestion Mitigation—0
A Rule-Based Behaviour Planner for Autonomous Driving—0
Quantum-tunnelling deep neural network for optical illusion recognition—0
Decentralized Semantic Traffic Control in AVs Using RL and DQN for Dynamic Roadblocks—0
A Multi-Stage Goal-Driven Network for Pedestrian Trajectory Prediction—0
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Benchmark Results

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