https://github.com/lssiair/sit
공식 코드Social Interpretable Tree for Pedestrian Trajectory Prediction
Papers with Code 아카이브
Trajectory Prediction
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 3
- 평가표
- 32
- 보존된 평가 기록
- 132
Trajectory Prediction is the problem of predicting the short-term (1-3 seconds) and long-term (3-5 seconds) spatial coordinates of various road-agents such as cars, buses, pedestrians, rickshaws, and animals, etc. These road-agents have different dynamic behaviors that may correspond to aggressive or conservative driving styles.
Source: Forecasting Trajectory and Behavior of Road-Agents Using Spectral Clustering in Graph-LSTMs
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/luciatesta97/generalized-simplicial-attention-neural-networks
공식 코드https://github.com/luigifilippochiara/Goal-SAR
공식 코드Goal-driven Self-Attentive Recurrent Networks for Trajectory Prediction
https://github.com/m-hasan-n/pooling
공식 코드https://github.com/magnux/MotionGAN
공식 코드https://github.com/makaruinah/shenet
공식 코드https://github.com/marc-rigter/polygrad-world-models
공식 코드https://github.com/meaten/flowchain-iccv2023
공식 코드Fast Inference and Update of Probabilistic Density Estimation on Trajectory Prediction
https://github.com/meaten/motionaug
공식 코드MotionAug: Augmentation with Physical Correction for Human Motion Prediction
https://github.com/mediabrain-sjtu/auxformer
공식 코드Auxiliary Tasks Benefit 3D Skeleton-based Human Motion Prediction
https://github.com/mediabrain-sjtu/collaborative-uncertainty
공식 코드Collaborative Uncertainty Benefits Multi-Agent Multi-Modal Trajectory Forecasting
https://github.com/mediabrain-sjtu/eqmotion
공식 코드EqMotion: Equivariant Multi-agent Motion Prediction with Invariant Interaction Reasoning
https://github.com/mediabrain-sjtu/groupnet
공식 코드GroupNet: Multiscale Hypergraph Neural Networks for Trajectory Prediction with Relational Reasoning
https://github.com/mediabrain-sjtu/led
공식 코드Leapfrog Diffusion Model for Stochastic Trajectory Prediction
https://github.com/mediabrain-sjtu/memonet
공식 코드Remember Intentions: Retrospective-Memory-based Trajectory Prediction
https://github.com/mediabrain-sjtu/spgsn
공식 코드Skeleton-Parted Graph Scattering Networks for 3D Human Motion Prediction
https://github.com/mengmengliu1998/LAformer
공식 코드LAformer: Trajectory Prediction for Autonomous Driving with Lane-Aware Scene Constraints
https://github.com/mengmengliu1998/gatraj
공식 코드GATraj: A Graph- and Attention-based Multi-Agent Trajectory Prediction Model
https://github.com/mipt-oulu/climat
공식 코드CLIMAT: Clinically-Inspired Multi-Agent Transformers for Knee Osteoarthritis Trajectory Forecasting
https://github.com/mkofinas/locs
공식 코드Roto-translated Local Coordinate Frames For Interacting Dynamical Systems
https://github.com/ml-jku/vnegnn
공식 코드https://github.com/mmahdavian/stpotr
공식 코드https://github.com/mohsenzand/motionflow
공식 코드Flow-based Spatio-Temporal Structured Prediction of Motion Dynamics
https://github.com/mousecpn/robot-trajectron
공식 코드Robot Trajectron: Trajectory Prediction-based Shared Control for Robot Manipulation
https://github.com/mulplue/mgf
공식 코드https://github.com/mzahana/drone_path_predictor_ros
공식 코드VECTOR: Velocity-Enhanced GRU Neural Network for Real-Time 3D UAV Trajectory Prediction
https://github.com/nachiket92/P2T
공식 코드Trajectory Forecasts in Unknown Environments Conditioned on Grid-Based Plans
https://github.com/nachiket92/PGP
공식 코드Multimodal Trajectory Prediction Conditioned on Lane-Graph Traversals
https://github.com/nachiket92/conv-social-pooling
공식 코드Convolutional Social Pooling for Vehicle Trajectory Prediction
https://github.com/nglaze00/SCoNe_GCN
공식 코드Principled Simplicial Neural Networks for Trajectory Prediction
https://github.com/nitinkamra1992/FQA
공식 코드Multi-agent Trajectory Prediction with Fuzzy Query Attention
https://github.com/nokpil/rain
공식 코드Learning Heterogeneous Interaction Strengths by Trajectory Prediction with Graph Neural Network
https://github.com/northocean/msn
공식 코드https://github.com/nubot-nudt/insmos
공식 코드InsMOS: Instance-Aware Moving Object Segmentation in LiDAR Data
https://github.com/nullmax-vision/hip-ad
공식 코드https://github.com/nvlabs/trajdata
공식 코드trajdata: A Unified Interface to Multiple Human Trajectory Datasets
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.