Motion Forecasting
67 papers with code • 1 benchmarks • 12 datasets
Motion forecasting is the task of predicting the location of a tracked object in the future
Benchmarks
These leaderboards are used to track progress in Motion Forecasting
| Trend | Dataset | Best Model | Paper | Code | Compare |
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Datasets
Argoverse
Waymo Open Motion Dataset
Argoverse-HD
Argoverse 2 Motion Forecasting
SinD
Argoverse 2 Sensor
Lyft Level 5 Prediction
Argoverse 2 Lidar
Most implemented papers
Frozen Transformers in Language Models Are Effective Visual Encoder Layers
ziqipang/lm4visualencoding
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This paper reveals that large language models (LLMs), despite being trained solely on textual data, are surprisingly strong encoders for purely visual tasks in the absence of language.
Learning Cooperative Trajectory Representations for Motion Forecasting
Specifically, we present V2X-Graph, the first interpretable and end-to-end learning framework for cooperative motion forecasting.
A Preprocessing and Evaluation Toolbox for Trajectory Prediction Research on the Drone Datasets
westny/dronalize
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The availability of high-quality datasets is crucial for the development of behavior prediction algorithms in autonomous vehicles.
The Trajectron: Probabilistic Multi-Agent Trajectory Modeling With Dynamic Spatiotemporal Graphs
StanfordASL/Trajectron
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ICCV 2019
Developing safe human-robot interaction systems is a necessary step towards the widespread integration of autonomous agents in society.
Human Motion Prediction via Spatio-Temporal Inpainting
magnux/MotionGAN
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First, we represent the data using a spatio-temporal tensor of 3D skeleton coordinates which allows formulating the prediction problem as an inpainting one, for which GANs work particularly well.
Structured Prediction Helps 3D Human Motion Modelling
eth-ait/spl
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ICCV 2019
This is implemented via a hierarchy of small-sized neural networks connected analogously to the kinematic chains in the human body as well as a joint-wise decomposition in the loss function.
Improving Movement Predictions of Traffic Actors in Bird's-Eye View Models using GANs and Differentiable Trajectory Rasterization
d-eremeev/SC-GAN
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One of the most critical pieces of the self-driving puzzle is the task of predicting future movement of surrounding traffic actors, which allows the autonomous vehicle to safely and effectively plan its future route in a complex world.
Towards Streaming Perception
While past work has studied the algorithmic trade-off between latency and accuracy, there has not been a clear metric to compare different methods along the Pareto optimal latency-accuracy curve.
Learning Lane Graph Representations for Motion Forecasting
uber-research/LaneGCN
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ECCV 2020
We propose a motion forecasting model that exploits a novel structured map representation as well as actor-map interactions.
One More Check: Making "Fake Background" Be Tracked Again
JudasDie/SOTS
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Eventually, it helps to reload the ``fake background'' and repair the broken tracklets.
