https://github.com/oliviazwy/dcgcn
공식 코드Dynamic Compositional Graph Convolutional Network for Efficient Composite Human Motion Prediction
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
Predict human activities in videos
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
Dynamic Compositional Graph Convolutional Network for Efficient Composite Human Motion Prediction
SmartRefine: A Scenario-Adaptive Refinement Framework for Efficient Motion Prediction
Predicting Long-Term Skeletal Motions by a Spatio-Temporal Hierarchical Recurrent Network
KP-RNN: A Deep Learning Pipeline for Human Motion Prediction and Synthesis of Performance Art
AGAR: Attention Graph-RNN for Adaptative Motion Prediction of Point Clouds of Deformable Objects
UncAD: Towards Safe End-to-end Autonomous Driving via Online Map Uncertainty
Quantifying Uncertainty in Motion Prediction with Variational Bayesian Mixture
Context-based Interpretable Spatio-Temporal Graph Convolutional Network for Human Motion Forecasting
Bidirectionally Deformable Motion Modulation For Video-based Human Pose Transfer
Latent Variable Sequential Set Transformers For Joint Multi-Agent Motion Prediction
MF-LAL: Drug Compound Generation Using Multi-Fidelity Latent Space Active Learning
LoRD: Adapting Differentiable Driving Policies to Distribution Shifts
SHARP: Shielding-Aware Robust Planning for Safe and Efficient Human-Robot Interaction
Sequential modeling of Sessions using Recurrent Neural Networks for Skip Prediction
PhysORD: A Neuro-Symbolic Approach for Physics-infused Motion Prediction in Off-road Driving
Towards Explainable Motion Prediction using Heterogeneous Graph Representations
A Neuro-Symbolic Approach for Enhanced Human Motion Prediction
Exploring Navigation Maps for Learning-Based Motion Prediction
Shifts 2.0: Extending The Dataset of Real Distributional Shifts
Predicting tongue motion in unlabeled ultrasound videos using convolutional LSTM neural network
Diverse Human Motion Prediction Guided by Multi-Level Spatial-Temporal Anchors
Gaussian Processes for Probabilistic Estimates of Earthquake Ground Shaking: A 1-D Proof-of-Concept
MTR-A: 1st Place Solution for 2022 Waymo Open Dataset Challenge -- Motion Prediction
MotionCNN: A Strong Baseline for Motion Prediction in Autonomous Driving
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.