Papers with Code 아카이브
Trajectory Prediction
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
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- 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/valeoai/cab
공식 코드https://github.com/valeoai/mf_awta
공식 코드https://github.com/viewsetting/unsupervised_sampling_promoting
공식 코드Unsupervised Sampling Promoting for Stochastic Human Trajectory Prediction
https://github.com/vincent-leguen/DILATE
공식 코드Shape and Time Distortion Loss for Training Deep Time Series Forecasting Models
https://github.com/vincent-leguen/STDL
공식 코드Shape and Time Distortion Loss for Training Deep Time Series Forecasting Models
https://github.com/vita-epfl/RRB
공식 코드Injecting Knowledge in Data-driven Vehicle Trajectory Predictors
https://github.com/vita-epfl/SVGNet
공식 코드https://github.com/vita-epfl/jrdb-traj
공식 코드JRDB-Traj: A Dataset and Benchmark for Trajectory Forecasting in Crowds
https://github.com/vita-epfl/monotransmotion
공식 코드Unified Human Localization and Trajectory Prediction with Monocular Vision
https://github.com/vita-epfl/multi-transmotion
공식 코드Multi-Transmotion: Pre-trained Model for Human Motion Prediction
https://github.com/vita-epfl/social-nce
공식 코드Social NCE: Contrastive Learning of Socially-aware Motion Representations
https://github.com/vita-epfl/social-transmotion
공식 코드https://github.com/vita-epfl/stay-on-track
공식 코드https://github.com/vita-epfl/unitraj
공식 코드UniTraj: A Unified Framework for Scalable Vehicle Trajectory Prediction
https://github.com/vivixiang/socialcvae
공식 코드SocialCVAE: Predicting Pedestrian Trajectory via Interaction Conditioned Latents
https://github.com/vtp-tl/d2-tpred
공식 코드D2-TPred: Discontinuous Dependency for Trajectory Prediction under Traffic Lights
https://github.com/wangzc0422/c2f-tp
공식 코드C2F-TP: A Coarse-to-Fine Denoising Framework for Uncertainty-Aware Trajectory Prediction
https://github.com/wangzcbruce/dhd
공식 코드https://github.com/wei-mao-2019/HisRepItself
공식 코드History Repeats Itself: Human Motion Prediction via Motion Attention
https://github.com/wei-mao-2019/LearnTrajDep
공식 코드Learning Trajectory Dependencies for Human Motion Prediction
https://github.com/wei-mao-2019/gsps
공식 코드Generating Smooth Pose Sequences for Diverse Human Motion Prediction
https://github.com/wei-mao-2019/wat
공식 코드Weakly-supervised Action Transition Learning for Stochastic Human Motion Prediction
https://github.com/westny/dronalize
공식 코드Toward Unified Practices in Trajectory Prediction Research on Bird's-Eye-View Datasets
https://github.com/westny/mtp-go
공식 코드MTP-GO: Graph-Based Probabilistic Multi-Agent Trajectory Prediction with Neural ODEs
https://github.com/woxihuanjiangguo/hydra-next
공식 코드Hydra-NeXt: Robust Closed-Loop Driving with Open-Loop Training
https://github.com/wtliao/DCENet
공식 코드Exploring Dynamic Context for Multi-path Trajectory Prediction
https://github.com/xhaughearl/haarmodic
공식 코드Multi-Resolution Haar Network: Enhancing human motion prediction via Haar transform
https://github.com/xiaolongtang23/hpnet
공식 코드HPNet: Dynamic Trajectory Forecasting with Historical Prediction Attention
https://github.com/xiaomiaozhang/Co-MTP
공식 코드https://github.com/xichennn/msma
공식 코드https://github.com/xichennn/v2i_trajectory_prediction
공식 코드Conformal Trajectory Prediction with Multi-View Data Integration in Cooperative Driving
https://github.com/xincoder/GRIP
공식 코드GRIP++: Enhanced Graph-based Interaction-aware Trajectory Prediction for Autonomous Driving
https://github.com/xingp/dgfnet
공식 코드Multi-Agent Trajectory Prediction with Difficulty-Guided Feature Enhancement Network
https://github.com/xingyu-song/4a
공식 코드An Animation-based Augmentation Approach for Action Recognition from Discontinuous Video
https://github.com/xinli0928/COVID-Xray
공식 코드COVID-MobileXpert: On-Device COVID-19 Patient Triage and Follow-up using Chest X-rays
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.