Through the use of Generative Adversarial Networks (GAN), a GAN is first trained to learn real flight paths, generating new flights from learned distributions. Experiments show that the new generated flights follow realistic patterns. Unlike trajectories generated by physical models, the proposed ...
With the advancement of deep learning techniques and computing power, combined with the development of new models, namely the Long Short-Term Memory (LSTM) [1] model for prediction and the more recent Generative Adversarial Network (GAN) [2] model for generation, systems are capable of processin...
This paper proposes a kind of vehicle trajectory generation algorithm based on Generative Adversarial Networks (GAN). The algorithm utilizes vehicle movement trajectory data to train both the discriminator and generator models to generate virtual trajectory data that matches the distribution of real ...
(2021) introduced a GAN model for trajectory generation and a vehicle turning model to adapt the prediction process in urban scenarios. During the dataset preparation, the complex spatial dependencies of road topology were addressed through vehicle coordinate transformation. The above-mentioned GAN-...
及VQ-VAE, VQ-GAN, VQ-DDPM介绍 4492 1 32:36 App 何凯明:Autoregressive Image Generation without Vector Quantizarion. 1334 -- 26:05 App Diffusion Models Learn Low-Dimensional Distributions via Subspace Clustering 1219 -- 27:50 App 扩散模型的记忆与泛化,过拟合 2736 1 37:10 App 随机分析1 :...
train_region_gan.py update and reopen the project Mar 13, 2023 Repository files navigation README Continuous Trajectory Generation Based on Two-Stage GAN (TS-TrajGen) Abstract Simulating the human mobility and generating large-scale trajectories are of great use in many real-world applications, suc...
LSTM-TrajGAN: A Deep Learning Approach to Trajectory Generation and Privacy Protection Abstract The prevalence of location-based services contributes to the explosive growth of individual-level location trajectory data and raises public concerns about privacy issues. In this research, we propose a novel...
(e.g., UAVs). However, in recent years, embedded systems have become more powerful, and optimization algorithms have become more efficient47. In UAV trajectory generation, MPC can fully exploit the system’s dynamics while respecting constraints imposed by the environment and the manipulation task...
UpdatedSep 28, 2024 TeX agrimgupta92/sgan Star842 Code Issues Pull requests Code for "Social GAN: Socially Acceptable Trajectories with Generative Adversarial Networks", Gupta et al, CVPR 2018 deep-learningpytorchgenerative-adversarial-networktrajectory-predictionsocial-navigationhuman-trajectory-prediction...
Large scale GPS trajectory generation using map based on two stage GAN Generating mobility trajectories with retained data utility Difftraj: Generating GPS trajectory with diffusion probabilistic model Recent advances in LLMs for trajectory mining Forecasting Where would i go next? large language model...