https://github.com/StanfordASL/Trajectron
공식 코드The Trajectron: Probabilistic Multi-Agent Trajectory Modeling With Dynamic Spatiotemporal Graphs
Papers with Code 아카이브
Trajectory Modeling
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 0
- 평가표
- 1
- 보존된 평가 기록
- 1
The equivalent of language modeling but for trajectories.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/YakshHaranwala/PTRAIL
공식 코드PTRAIL -- A python package for parallel trajectory data preprocessing
https://github.com/airalcorn2/baller2vecplusplus
공식 코드baller2vec++: A Look-Ahead Multi-Entity Transformer For Modeling Coordinated Agents
https://github.com/changyanchuan/trajcl
공식 코드Contrastive Trajectory Similarity Learning with Dual-Feature Attention
https://github.com/chimeraki/Multilayer-Trajectory-Clustering
공식 코드Multi-layer Trajectory Clustering: A Network Algorithm for Disease Subtyping
https://github.com/logan-lin/gtm
공식 코드UVTM: Universal Vehicle Trajectory Modeling with ST Feature Domain Generation
https://github.com/logan-lin/uvtm
공식 코드UVTM: Universal Vehicle Trajectory Modeling with ST Feature Domain Generation
https://github.com/philips-labs/demo-clustering-longitudinal-data
공식 코드Clustering of longitudinal data: A tutorial on a variety of approaches
https://github.com/roggirg/AutoBots
공식 코드Latent Variable Sequential Set Transformers For Joint Multi-Agent Motion Prediction
https://github.com/sharkwyf/cgdt
공식 코드Critic-Guided Decision Transformer for Offline Reinforcement Learning
https://github.com/sotif-avlab/sind
공식 코드https://github.com/tsinghua-fib-lab/trajagent
공식 코드TrajAgent: An Agent Framework for Unified Trajectory Modelling
https://github.com/zcsrenlongz/deblur4dgs
공식 코드Deblur4DGS: 4D Gaussian Splatting from Blurry Monocular Video
https://github.com/charleshsc/HarmoDT
Q-value Regularized Transformer for Offline Reinforcement Learning
https://github.com/charleshsc/qt
Q-value Regularized Transformer for Offline Reinforcement Learning
https://github.com/kfragkedaki/pedestrian_project
https://github.com/large-trajectory-model/atm
https://github.com/myniuuu/mofa-video
DragNUWA: Fine-grained Control in Video Generation by Integrating Text, Image, and Trajectory
https://github.com/vita-epfl/unitraj
Latent Variable Sequential Set Transformers For Joint Multi-Agent Motion Prediction
https://github.com/westny/dronalize
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.