Awesome-Human-Pose-Prediction
A selection of State Of The Art research papers (and code) on human trajectory prediction (forecasting). Papers marked with [W] are workshop papers.
Maintainers: Karttikeya Mangalam
Contributing: Please feel free to pull requests to add new resources or suggest addditions or changes to the list. While proposing a new addition, please keep in mind the following principles:
- The work has been accepted in a reputable peer reviewed publication venue.
- An opensource link to the paper pdf is attached (as far as possible).
- Code for the paper is linked (if made opensource by the authors).
Email: mangalam@cs.{berkeley,stanford).edu
Datasets
- Human3.6M: Large Scale Datasets and Predictive Methods for 3D Human Sensing in Natural Environments [Paper]
- Stanford Drone Dataset (SDD): Learning Social Etiquette: Human Trajectory Understanding in Crowded Scenes [Paper] [Leaderboard]
Papers
As End in Itself
-
From Goals, Waypoints & Paths To Long Term Human Trajectory Forecasting [Paper]
-
It Is Not the Journey but the Destination: Endpoint Conditioned Trajectory Prediction [Paper]
-
Trajectron++: Dynamically-Feasible Trajectory Forecasting With Heterogeneous Data [Paper]
-
Interaction-Based Trajectory Prediction Over a Hybrid Traffic Graph [paper]
-
Map-Adaptive Goal-Based Trajectory Prediction [paper]
-
Interaction-Aware Trajectory Prediction based on a 3D Spatio-Temporal Tensor Representation using Convolutional–Recurrent Neural Networks [paper]
-
DROGON: A Trajectory Prediction Model based on Intention-Conditioned Behavior Reasoning [Paper]
-
Discrete Residual Flow for Probabilistic Pedestrian Behavior Prediction [Paper]
-
Social-VRNN: One-Shot Multi-modal Trajectory Prediction for Interacting Pedestrians [Paper]
-
Leveraging Neural Network Gradients within Trajectory Optimization for Proactive Human-Robot Interactions [Paper]
-
Social NCE: Contrastive Learning of Socially-aware Motion Representations [Paper]
-
Multimodal Deep Generative Models for Trajectory Prediction: A Conditional Variational Autoencoder Approach [Paper]
-
Risk-Sensitive Sequential Action Control with Multi-Modal Human Trajectory Forecasting for Safe Crowd-Robot Interaction [Paper]
-
Deep Learning for Vision-based Prediction: A Survey [Paper]
-
Probabilistic Crowd GAN: Multimodal Pedestrian Trajectory Prediction Using a Graph Vehicle-Pedestrian Attention Network [Paper]
-
Semantics for Robotic Mapping, Perception and Interaction: A Survey [Paper]
-
Benchmark for Evaluating Pedestrian Action Prediction[Paper]
-
Probabilistic Tracklet Scoring and Inpainting for Multiple Object Tracking [Paper]
-
Pedestrian Behavior Prediction via Multitask Learning and Categorical Interaction Modeling [Paper]
-
Graph-SIM: A Graph-based Spatiotemporal Interaction Modelling for Pedestrian Action Prediction [Paper]
-
Haar Wavelet based Block Autoregressive Flows for Trajectories [Paper]
-
Imitative Planning using Conditional Normalizing Flow [Paper]
-
TNT: Target-driveN Trajectory Prediction [Paper]
-
SimAug: Learning Robust Representations from Simulation for Trajectory Prediction [Paper]
-
SoPhie: An Attentive GAN for Predicting Paths Compliant to Social and Physical Constraints [Paper]
-
Social GAN: Socially Acceptable Trajectories With Generative Adversarial Networks [Paper]
-
DESIRE: Distant Future Prediction in Dynamic Scenes With Interacting Agents [Paper]
-
Predicting Whole Body Motion Trajectories using Conditional Neural Movement Primitives [Paper] [W]
-
Anticipating Human Intention for Full-Body Motion Prediction [Paper] [W]
-
Human Motion Prediction With Graph Neural Networks [Paper] [W]
-
Action-Agnostic Human Pose Forecasting [Paper]
-
Human Torso Pose Forecasting in the Real World [Paper]
-
Imitation Learning for Human Pose Prediction [Paper]
-
Disentangling Human Dynamics for Pedestrian Locomotion Forecasting with Noisy Supervision [Paper]
-
Predicting 3D Human Dynamics from Video [Paper]
-
Recurrent Network Models for Human Dynamics [Paper]
-
Structural-RNN: Deep Learning on Spatio-Temporal Graphs [Paper]
-
Learning Trajectory Dependencies for Human Motion Prediction [Paper]
-
Anticipating many futures: Online human motion prediction and generation for human-robot interaction [Paper]
-
Teaching Robots to Predict Human Motion [Paper]
-
Deep representation learning for human motion prediction and classification [Paper]
-
On human motion prediction using recurrent neural networks [Paper]
-
Few-Shot Human Motion Prediction via Meta-learning [Paper]
-
Efficient convolutional hierarchical autoencoder for human motion prediction [Paper]
-
Learning Human Motion Models for Long-term Predictions [Paper]
-
Long-Term Human Motion Prediction by Modeling Motion Context and Enhancing Motion Dynamic [Paper]
-
Context-aware Human Motion Prediction [Paper]
-
Adversarial Geometry-Aware Human Motion Prediction [Paper]
-
Convolutional Sequence to Sequence Model for Human Dynamics [Paper]
-
QuaterNet: A Quaternion-based Recurrent Model for Human Motion [Paper]
-
BiHMP-GAN: Bidirectional 3D Human Motion Prediction GAN [Paper]
-
Human Motion Modeling using DVGANs [Paper]
-
Human Motion Prediction using Semi-adaptable Neural Networks [Paper]
-
A Neural Temporal Model for Human Motion Prediction [Paper]
-
Modeling Human Motion with Quaternion-based Neural Networks [Paper]
-
Human Motion Prediction via Learning Local Structure Representations and Temporal Dependencies [Paper]
-
VRED: A Position-Velocity Recurrent Encoder-Decoder for Human Motion Prediction [Paper]
-
EAN: Error Attenuation Network for Long-term Human Motion Prediction [Paper]
-
Structured Prediction Helps 3D Human Motion Modelling [Paper]
-
Forecasting Human Dynamics from Static Images [Paper]
-
HP-GAN: Probabilistic 3D human motion prediction via GAN [Paper]
-
Learning Latent Representations of 3D Human Pose with Deep Neural Networks [Paper]
-
A Recurrent Variational Autoencoder for Human Motion Synthesis [Paper]
-
Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling [Paper]
-
Combining Recurrent Neural Networks and Adversarial Training for Human Motion Synthesis and Control [Paper]
-
PISEP2: Pseudo Image Sequence Evolution based 3D Pose Prediction [Paper]
-
Human Motion Prediction via Spatio-Temporal Inpainting [Paper]
-
Spatiotemporal Co-attention Recurrent Neural Networks for Human-Skeleton Motion Prediction [Paper]
-
Human Pose Forecasting via Deep Markov Models [Paper]
-
Auto-Conditioned Recurrent Networks For Extended Complex Human Motion Synthesis [Paper]
-
Predicting Long-Term Skeletal Motions by a Spatio-Temporal Hierarchical Recurrent Network [Paper]
As a Subtask
- The Pose Knows: Video Forecasting by Generating Pose Futures [Paper]
- I-Planner: Intention-Aware Motion Planning Using Learning Based Human Motion Prediction [Paper]
- Language2Pose: Natural Language Grounded Pose Forecasting [Paper]
- Long-Term Video Generation of Multiple Futures Using Human Poses [Paper]
- Predicting body movements for person identification under different walking conditions [Paper]