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Found 9 papers, 0 papers with code
MVFuseNet: Improving End-to-End Object Detection and Motion Forecasting through Multi-View Fusion of LiDAR Data
In this work, we propose \textit{MVFuseNet}, a novel end-to-end method for joint object detection and motion forecasting from a temporal sequence of LiDAR data.
LiRaNet: End-to-End Trajectory Prediction using Spatio-Temporal Radar Fusion
In this paper, we present LiRaNet, a novel end-to-end trajectory prediction method which utilizes radar sensor information along with widely used lidar and high definition (HD) maps.
RV-FuseNet: Range View Based Fusion of Time-Series LiDAR Data for Joint 3D Object Detection and Motion Forecasting
We show that our approach significantly improves motion forecasting performance over the existing state-of-the-art.
LaserFlow: Efficient and Probabilistic Object Detection and Motion Forecasting
In this work, we present LaserFlow, an efficient method for 3D object detection and motion forecasting from LiDAR.
Sensor Fusion for Joint 3D Object Detection and Semantic Segmentation
In this paper, we present an extension to LaserNet, an efficient and state-of-the-art LiDAR based 3D object detector.
LaserNet: An Efficient Probabilistic 3D Object Detector for Autonomous Driving
The efficiency results from processing LiDAR data in the native range view of the sensor, where the input data is naturally compact.
Resolving Language and Vision Ambiguities Together: Joint Segmentation & Prepositional Attachment Resolution in Captioned Scenes
Our approach produces a diverse set of plausible hypotheses for both semantic segmentation and prepositional phrase attachment resolution that are then jointly reranked to select the most consistent pair.
