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Found 12 papers, 10 papers with code
Certified Human Trajectory Prediction
Trajectory prediction plays an essential role in autonomous vehicles.
Social-Transmotion: Promptable Human Trajectory Prediction
We translate the idea of a prompt from Natural Language Processing (NLP) to the task of human trajectory prediction, where a prompt can be a sequence of x-y coordinates on the ground, bounding boxes in the image plane, or body pose keypoints in either 2D or 3D.
JRDB-Traj: A Dataset and Benchmark for Trajectory Forecasting in Crowds
To address this, we introduce a novel dataset for end-to-end trajectory forecasting, facilitating the evaluation of models in scenarios involving less-than-ideal preceding modules such as tracking.
Toward Reliable Human Pose Forecasting with Uncertainty
Recently, there has been an arms race of pose forecasting methods aimed at solving the spatio-temporal task of predicting a sequence of future 3D poses of a person given a sequence of past observed ones.
A generic diffusion-based approach for 3D human pose prediction in the wild
Predicting 3D human poses in real-world scenarios, also known as human pose forecasting, is inevitably subject to noisy inputs arising from inaccurate 3D pose estimations and occlusions.
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Human Pose Forecasting
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Pedestrian 3D Bounding Box Prediction
Safety is still the main issue of autonomous driving, and in order to be globally deployed, they need to predict pedestrians' motions sufficiently in advance.
A Shared Representation for Photorealistic Driving Simulators
We build on successful cGAN models to propose a new semantically-aware discriminator that better guides the generator.
Vehicle trajectory prediction works, but not everywhere
We further show that the generated scenes (i) are realistic since they do exist in the real world, and (ii) can be used to make existing models more robust, yielding 30-40 reductions in the off-road rate.
SVG-Net: An SVG-based Trajectory Prediction Model
Finally, we illustrate how, by using SVG, one can benefit from datasets and advancements in other research fronts that also utilize the same input format.
Are socially-aware trajectory prediction models really socially-aware?
An attack is a small yet carefully-crafted perturbations to fail predictors.
Pedestrian Intention Prediction: A Multi-task Perspective
This work tries to solve this problem by jointly predicting the intention and visual states of pedestrians.
LSTM-Based ECG Classification for Continuous Monitoring on Personal Wearable Devices
Conclusion: In contrast to many compute-intensive deep-learning based approaches, the proposed algorithm is lightweight, and therefore, brings continuous monitoring with accurate LSTM-based ECG classification to wearable devices.
