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motion prediction

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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/mohsenzand/reschunk

Multiscale Residual Learning of Graph Convolutional Sequence Chunks for Human Motion Prediction

https://github.com/motional/nuplan-devkit

NuPlan: A closed-loop ML-based planning benchmark for autonomous vehicles

https://github.com/nageshpindi/human-motion-prediction-master

On human motion prediction using recurrent neural networks

https://github.com/nikeke19/safe-mult-rl

Motion Transformer with Global Intention Localization and Local Movement Refinement

https://github.com/open3da/ll3da

MotionGPT: Human Motion as a Foreign Language

https://github.com/openmeshlab/meshxl

MotionGPT: Human Motion as a Foreign Language

https://github.com/pranav-chib/trajimpute

EqMotion: Equivariant Multi-agent Motion Prediction with Invariant Interaction Reasoning

https://github.com/seu-zxj/llm-augmented-mtr

Large Language Models Powered Context-aware Motion Prediction in Autonomous Driving

https://github.com/stepankonev/waymo-motion-prediction-challenge-2022-multipath-plus-plus

MultiPath++: Efficient Information Fusion and Trajectory Aggregation for Behavior Prediction

https://github.com/umich-curly/3dmapping

MotionNet: Joint Perception and Motion Prediction for Autonomous Driving Based on Bird's Eye View Maps

https://github.com/vita-epfl/unitraj

Latent Variable Sequential Set Transformers For Joint Multi-Agent Motion Prediction

https://github.com/walzimmer/bat-3d

3D BAT: A Semi-Automatic, Web-based 3D Annotation Toolbox for Full-Surround, Multi-Modal Data Streams

https://github.com/wangwenxi-handsome/joint-multipathpp

MPA: MultiPath++ Based Architecture for Motion Prediction

https://github.com/wenkaip-1836890/pyromid_l5prediction

One Thousand and One Hours: Self-driving Motion Prediction Dataset

https://github.com/westny/dronalize

INTERACTION Dataset: An INTERnational, Adversarial and Cooperative moTION Dataset in Interactive Driving Scenarios with Semantic Maps

https://github.com/wzzheng/doe

GPD-1: Generative Pre-training for Driving

https://github.com/xcyan/eccv18_mtvae

MT-VAE: Learning Motion Transformations to Generate Multimodal Human Dynamics

https://github.com/xincoder/GRIP_Trajectory

GRIP++: Enhanced Graph-based Interaction-aware Trajectory Prediction for Autonomous Driving

https://github.com/xiuyu0000/new_papers_codes/tree/main/rbpn

Tracking without bells and whistles

https://github.com/zhanwei-z/g2ltraj

Social-STGCNN: A Social Spatio-Temporal Graph Convolutional Neural Network for Human Trajectory Prediction

https://github.com/zhejz/trafficbotsv1.5

Scene Transformer: A unified architecture for predicting multiple agent trajectories

https://github.com/zqzqz/AdvTrajectoryPrediction

GRIP++: Enhanced Graph-based Interaction-aware Trajectory Prediction for Autonomous Driving

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.