Papers with Code 아카이브

Trajectory Prediction

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법 전체 데이터셋

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/sharmasushil/navigating-uncertainty-trajectory-prediction

공식 코드

Navigating Uncertainty: The Role of Short-Term Trajectory Prediction in Autonomous Vehicle Safety

https://github.com/shuaishiliu/SGCN

공식 코드

SGCN:Sparse Graph Convolution Network for Pedestrian Trajectory Prediction

https://github.com/shuijing725/crowdnav_sim2real_turtlebot

공식 코드

Intention Aware Robot Crowd Navigation with Attention-Based Interaction Graph

https://github.com/sibotian96/TransFusion

공식 코드

TransFusion: A Practical and Effective Transformer-based Diffusion Model for 3D Human Motion Prediction

https://github.com/simple316/mstformer

공식 코드

MSTFormer: Motion Inspired Spatial-temporal Transformer with Dynamic-aware Attention for long-term Vessel Trajectory Prediction

https://github.com/sirui-xu/stars

공식 코드

Diverse Human Motion Prediction Guided by Multi-Level Spatial-Temporal Anchors

https://github.com/sisl/interpretableselfawareprediction

공식 코드

Interpretable Self-Aware Neural Networks for Robust Trajectory Prediction

https://github.com/sisl/lopr

공식 코드

LOPR: Latent Occupancy PRediction using Generative Models

https://github.com/sisl/perceptionadaptivestresstesting

공식 코드

How Do We Fail? Stress Testing Perception in Autonomous Vehicles

https://github.com/sisl/sceneinformer

공식 코드

Scene Informer: Anchor-based Occlusion Inference and Trajectory Prediction in Partially Observable Environments

https://github.com/sonsang/diffidm

공식 코드

Gradient-based Trajectory Optimization with Parallelized Differentiable Traffic Simulation

https://github.com/sotif-avlab/sind

공식 코드

SIND: A Drone Dataset at Signalized Intersection in China

https://github.com/sshaoshuai/mtr

공식 코드

Motion Transformer with Global Intention Localization and Local Movement Refinement

https://github.com/stanfordasl/psu-tf

공식 코드

Propagating State Uncertainty Through Trajectory Forecasting

https://github.com/tdavchev/structured-trajectory-prediction

공식 코드

Learning Structured Representations of Spatial and Interactive Dynamics for Trajectory Prediction in Crowded Scenes

https://github.com/tecsar-uncc/carolinas_dataset

공식 코드

A POV-based Highway Vehicle Trajectory Dataset and Prediction Architecture

https://github.com/tecsar-uncc/pishguve

공식 코드

A POV-based Highway Vehicle Trajectory Dataset and Prediction Architecture

https://github.com/tecsar-uncc/tsgad

공식 코드

An Exploratory Study on Human-Centric Video Anomaly Detection through Variational Autoencoders and Trajectory Prediction

https://github.com/tedhuang96/gst

공식 코드

Learning Sparse Interaction Graphs of Partially Detected Pedestrians for Trajectory Prediction

https://github.com/tedhuang96/mifwlstm

공식 코드

Long-term Pedestrian Trajectory Prediction using Mutable Intention Filter and Warp LSTM

https://github.com/thisishale/socrec

공식 코드

Socially-Informed Reconstruction for Pedestrian Trajectory Forecasting

https://github.com/tib-k330/pmm-net

공식 코드

PMM-Net: Single-stage Multi-agent Trajectory Prediction with Patching-based Embedding and Explicit Modal Modulation

https://github.com/tileb1/motion-prediction-tim

공식 코드

Motion Prediction Using Temporal Inception Module

https://github.com/tl-qz/trajdiffuse

공식 코드

TrajDiffuse: A Conditional Diffusion Model for Environment-Aware Trajectory Prediction

https://github.com/tmralmeida/thor-magni-actions

공식 코드

THÖR-MAGNI Act: Actions for Human Motion Modeling in Robot-Shared Industrial Spaces

https://github.com/tommygong08/msif

공식 코드

Leveraging Multi-stream Information Fusion for Trajectory Prediction in Low-illumination Scenarios: A Multi-channel Graph Convolutional Approach

https://github.com/tosshero/3d_perception

공식 코드

Lightweight LiDAR-Camera 3D Dynamic Object Detection and Multi-Class Trajectory Prediction

https://github.com/tosshero/ros_packages

공식 코드

Lightweight LiDAR-Camera 3D Dynamic Object Detection and Multi-Class Trajectory Prediction

https://github.com/tri-ml/haicu

공식 코드

Heterogeneous-Agent Trajectory Forecasting Incorporating Class Uncertainty

https://github.com/trungmanhhuynh/GPRAR

공식 코드

GPRAR: Graph Convolutional Network based Pose Reconstruction and Action Recognition for Human Trajectory Prediction

https://github.com/tumftm/snapshot

공식 코드

Snapshot: Towards Application-centered Models for Pedestrian Trajectory Prediction in Urban Traffic Environments

https://github.com/uber-research/LaneGCN

공식 코드

Learning Lane Graph Representations for Motion Forecasting

https://github.com/una-dinosauria/human-motion-prediction

공식 코드

On human motion prediction using recurrent neural networks

https://github.com/uzh-rpg/event_based_ping_pong_ball_trajectory_prediction

공식 코드

Egocentric Event-Based Vision for Ping Pong Ball Trajectory Prediction

https://github.com/v0lta/Complex-gated-recurrent-neural-networks

공식 코드

Complex Gated Recurrent Neural Networks

https://github.com/vacany/let-it-flow

공식 코드

Let-It-Flow: Simultaneous Optimization of 3D Flow and Object Clustering

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