motion prediction
187 papers with code • 0 benchmarks • 13 datasets
Benchmarks
These leaderboards are used to track progress in motion prediction
Libraries
Use these libraries to find motion prediction models and implementationsDatasets
UCY
Waymo Open Motion Dataset
Argoverse 2 Motion Forecasting
Expi
SinD
GTA-IM Dataset
NTU RGB+D 2D
Lyft Level 5 Prediction
Latest papers with no code
MoST: Multi-modality Scene Tokenization for Motion Prediction
This symbolic representation is a high-level abstraction of the real world, which may render the motion prediction model vulnerable to perception errors (e. g., failures in detecting open-vocabulary obstacles) while missing salient information from the scene context (e. g., poor road conditions).
MAP-Former: Multi-Agent-Pair Gaussian Joint Prediction
This paper addresses that gap by introducing a novel approach to motion prediction, focusing on predicting agent-pair covariance matrices in a ``scene-centric'' manner, which can then be used to model Gaussian joint PDFs for all agent-pairs in a scene.
PhysDreamer: Physics-Based Interaction with 3D Objects via Video Generation
Unlike unconditional or text-conditioned dynamics generation, action-conditioned dynamics requires perceiving the physical material properties of objects and grounding the 3D motion prediction on these properties, such as object stiffness.
FipTR: A Simple yet Effective Transformer Framework for Future Instance Prediction in Autonomous Driving
The future instance prediction from a Bird's Eye View(BEV) perspective is a vital component in autonomous driving, which involves future instance segmentation and instance motion prediction.
State-space Decomposition Model for Video Prediction Considering Long-term Motion Trend
In this paper, we propose a state-space decomposition stochastic video prediction model that decomposes the overall video frame generation into deterministic appearance prediction and stochastic motion prediction.
SparseAD: Sparse Query-Centric Paradigm for Efficient End-to-End Autonomous Driving
End-to-End paradigms use a unified framework to implement multi-tasks in an autonomous driving system.
Two-Person Interaction Augmentation with Skeleton Priors
Close and continuous interaction with rich contacts is a crucial aspect of human activities (e. g. hugging, dancing) and of interest in many domains like activity recognition, motion prediction, character animation, etc.
Towards more realistic human motion prediction with attention to motion coordination
However, the motion coordination, a global joint relation reflecting the simultaneous cooperation of all joints, is usually weakened because it is learned from part to whole progressively and asynchronously.
Quantifying Uncertainty in Motion Prediction with Variational Bayesian Mixture
In this paper, we propose the Sequential Neural Variational Agent (SeNeVA), a generative model that describes the distribution of future trajectories for a single moving object.
SC4D: Sparse-Controlled Video-to-4D Generation and Motion Transfer
Recent advances in 2D/3D generative models enable the generation of dynamic 3D objects from a single-view video.
