Journals starting with wad2

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

WAD23 * *Autonomous Driving
* Does Image Anonymization Impact Computer Vision Training?
* DPPD: Deformable Polar Polygon Object Detection
* EGA-Depth: Efficient Guided Attention for Self-Supervised Multi-Camera Depth Estimation
* Exploiting the Complementarity of 2D and 3D Networks to Address Domain-Shift in 3D Semantic Segmentation
* FUTR3D: A Unified Sensor Fusion Framework for 3D Detection
* HazardNet: Road Debris Detection by Augmentation of Synthetic Models
* Improvements to Image Reconstruction-Based Performance Prediction for Semantic Segmentation in Highly Automated Driving
* Improving Rare Classes on nuScenes LiDAR segmentation Through Targeted Domain Adaptation
* Joint Camera and LiDAR Risk Analysis
* LiDAR-Based Localization on Highways Using Raw Data and Pole-Like Object Features
* MobileDeRainGAN: An Efficient Semi-Supervised Approach to Single Image Rain Removal for Task-Driven Applications
* MotionTrack: End-to-End Transformer-based Multi-Object Tracking with LiDAR-Camera Fusion
* RadarGNN: Transformation Invariant Graph Neural Network for Radar-based Perception
* TorchSparse++: Efficient Point Cloud Engine
* Training Strategies for Vision Transformers for Object Detection
* Ultra-Sonic Sensor based Object Detection for Autonomous Vehicles
17 for WAD23

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