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Found 5 papers, 4 papers with code
Diverse and Admissible Trajectory Prediction through Multimodal Context Understanding
Multi-agent trajectory forecasting in autonomous driving requires an agent to accurately anticipate the behaviors of the surrounding vehicles and pedestrians, for safe and reliable decision-making.
IFSeg: Image-free Semantic Segmentation via Vision-Language Model
In this paper, we introduce a novel image-free segmentation task where the goal is to perform semantic segmentation given only a set of the target semantic categories, but without any task-specific images and annotations.
LaPred: Lane-Aware Prediction of Multi-Modal Future Trajectories of Dynamic Agents
In this paper, we address the problem of predicting the future motion of a dynamic agent (called a target agent) given its current and past states as well as the information on its environment.
Diverse and Admissible Trajectory Forecasting through Multimodal Context Understanding
Multi-agent trajectory forecasting in autonomous driving requires an agent to accurately anticipate the behaviors of the surrounding vehicles and pedestrians, for safe and reliable decision-making.
Sequence-to-Sequence Prediction of Vehicle Trajectory via LSTM Encoder-Decoder Architecture
We employ the encoder-decoder architecture which analyzes the pattern underlying in the past trajectory using the long short-term memory (LSTM) based encoder and generates the future trajectory sequence using the LSTM based decoder.
