WAD21
* *Autonomous Driving
* Accurate 3D Object Detection using Energy-Based Models
* Latent Space Regularization for Unsupervised Domain Adaptation in Semantic Segmentation
* LCCNet: LiDAR and Camera Self-Calibration using Cost Volume Network
* Multi-task Learning with Attention for End-to-end Autonomous Driving
* MVFuseNet: Improving End-to-End Object Detection and Motion Forecasting through Multi-View Fusion of LiDAR Data
* Occlusion Guided Scene Flow Estimation on 3D Point Clouds
* RAD: Realtime and Accurate 3D Object Detection on Embedded Systems
* Rethinking of Radar's Role: A Camera-Radar Dataset and Systematic Annotator via Coordinate Alignment
* Semi-synthesis: A fast way to produce effective datasets for stereo matching
* Soft Cross Entropy Loss and Bottleneck Tri-Cost Volume For Efficient Stereo Depth Prediction
* Video Class Agnostic Segmentation Benchmark for Autonomous Driving
12 for WAD21
WAD22
* *Autonomous Driving
* Anomaly Detection in Autonomous Driving: A Survey
* CarlaScenes: A synthetic dataset for odometry in autonomous driving
* H-Net: Unsupervised Attention-based Stereo Depth Estimation Leveraging Epipolar Geometry
* K-Lane: Lidar Lane Dataset and Benchmark for Urban Roads and Highways
* Multi-level Domain Adaptation for Lane Detection
* Multi-modal 3D Human Pose Estimation with 2D Weak Supervision in Autonomous Driving
* MUTR3D: A Multi-camera Tracking Framework via 3D-to-2D Queries
* Performance Prediction for Semantic Segmentation by a Self-Supervised Image Reconstruction Decoder
* PointMotionNet: Point-Wise Motion Learning for Large-Scale LiDAR Point Clouds Sequences
* Proposal-free Lidar Panoptic Segmentation with Pillar-level Affinity
* PseudoProp: Robust Pseudo-Label Generation for Semi-Supervised Object Detection in Autonomous Driving Systems
* Raising context awareness in motion forecasting
* Reconstruct from Top View: A 3D Lane Detection Approach based on Geometry Structure Prior
* RoadSaW: A Large-Scale Dataset for Camera-Based Road Surface and Wetness Estimation
* Scene Representation in Bird's-Eye View from Surrounding Cameras with Transformers
* Towards Robust Semantic Segmentation of Accident Scenes via Multi-Source Mixed Sampling and Meta-Learning
* TripletTrack: 3D Object Tracking using Triplet Embeddings and LSTM
* Trust Your IMU: Consequences of Ignoring the IMU Drift
19 for WAD22