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Found 11 papers, 5 papers with code
S4TP: Social-Suitable and Safety-Sensitive Trajectory Planning for Autonomous Vehicles
To effectively assess the risks prevailing in the vicinity of AVs in social interactive traffic scenarios and achieve safe autonomous driving, this article proposes a social-suitable and safety-sensitive trajectory planning (S4TP) framework.
ModaLink: Unifying Modalities for Efficient Image-to-PointCloud Place Recognition
Experimental results on the KITTI dataset show that our proposed methods achieve state-of-the-art performance while running in real time.
Distilling Temporal Knowledge with Masked Feature Reconstruction for 3D Object Detection
Ultimately, we utilize this reconstruction target to reconstruct the student features.
Cam4DOcc: Benchmark for Camera-Only 4D Occupancy Forecasting in Autonomous Driving Applications
Furthermore, the standardized evaluation protocol for preset multiple tasks is also provided to compare the performance of all the proposed baselines on present and future occupancy estimation with respect to objects of interest in autonomous driving scenarios.
WeatherDepth: Curriculum Contrastive Learning for Self-Supervised Depth Estimation under Adverse Weather Conditions
In this paper, we propose WeatherDepth, a self-supervised robust depth estimation model with curriculum contrastive learning, to tackle performance degradation in complex weather conditions.
I2P-Rec: Recognizing Images on Large-scale Point Cloud Maps through Bird's Eye View Projections
The experimental results evaluated on the KITTI dataset show that, with only a small set of training data, I2P-Rec achieves recall rates at Top-1\% over 80\% and 90\%, when localizing monocular and stereo images on point cloud maps, respectively.
SuperFusion: Multilevel LiDAR-Camera Fusion for Long-Range HD Map Generation
However, current works are based on raw data or network feature-level fusion and only consider short-range HD map generation, limiting their deployment to realistic autonomous driving applications.
On the Re-Solving Heuristic for (Binary) Contextual Bandits with Knapsacks
To the best of our knowledge, this is the first $\widetilde O(1)$ regret result in the CBwK problem regardless of information feedback models.
A Reinforcement Learning Approach in Multi-Phase Second-Price Auction Design
First, from the seller's perspective, we need to efficiently explore the environment in the presence of potentially nontruthful bidders who aim to manipulates seller's policy.
Efficient Spatial-Temporal Information Fusion for LiDAR-Based 3D Moving Object Segmentation
We also use a point refinement module via 3D sparse convolution to fuse the information from both LiDAR range image and point cloud representations and reduce the artifacts on the borders of the objects.
No-regret Learning in Repeated First-Price Auctions with Budget Constraints
Recently the online advertising market has exhibited a gradual shift from second-price auctions to first-price auctions.
