Nothing Special   »   [go: up one dir, main page]

Zhu et al., 2021 - Google Patents

Fast Adaptive Character Animation Synthesis Based on Greedy Algorithm

Zhu et al., 2021

View PDF @Full View
Document ID
9139610668770105546
Author
Zhu Y
Chen Q
Liu J
Tian X
Publication year
Publication venue
Complexity

External Links

Snippet

On the premise of ensuring the animation effect and real‐time performance, it is of great significance and value for large‐scale group character animation synthesis how to reduce the disaster coincidence degree among various models of fast adaptive character animation …
Continue reading at onlinelibrary.wiley.com (PDF) (other versions)

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00—Subject matter not provided for in other groups of this subclass
    • G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computer systems based on biological models
    • G06N3/02—Computer systems based on biological models using neural network models
    • G06N3/08—Learning methods
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/50—Computer-aided design
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/6267—Classification techniques
    • G06K9/6268—Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00—Computer systems utilising knowledge based models
    • G06N5/02—Knowledge representation
    • G06N5/022—Knowledge engineering, knowledge acquisition
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00—Computer systems utilising knowledge based models
    • G06N5/04—Inference methods or devices
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis

Similar Documents

Publication Publication Date Title
EP3620990A1 (en) Capturing network dynamics using dynamic graph representation learning
Ramu et al. A survey of machine learning techniques in structural and multidisciplinary optimization
Song et al. Ensemble reinforcement learning: A survey
Zhao et al. Usersim: User simulation via supervised generativeadversarial network
Yuan et al. UniST: A Prompt-Empowered Universal Model for Urban Spatio-Temporal Prediction
Xu et al. Dynamic-group-aware networks for multi-agent trajectory prediction with relational reasoning
Tibaldi et al. Bayesian optimization for QAOA
Shao et al. How does traffic environment quantitatively affect the autonomous driving prediction?
Westny et al. Diffusion-based environment-aware trajectory prediction
Zhu et al. Fast Adaptive Character Animation Synthesis Based on Greedy Algorithm
Chen et al. Neural task planning with and–or graph representations
Li et al. Multi-Agent Dynamic Relational Reasoning for Social Robot Navigation
Luo et al. Improving data analytics with fast and adaptive regularization
Tang et al. A deep map transfer learning method for face recognition in an unrestricted smart city environment
Shao et al. Self-aware trajectory prediction for safe autonomous driving
Zhao et al. Large scale instance segmentation of outdoor environment based on improved YOLACT
Huang Improved quantum particle swarm optimization for mangroves classification
Wang et al. Spatio-temporal branching for motion prediction using motion increments
Kulvicius et al. One-shot path planning for multi-agent systems using fully convolutional neural network
Xia et al. Graph Wasserstein autoencoder-based asymptotically optimal motion planning with kinematic constraints for robotic manipulation
Mai et al. From Efficient Multimodal Models to World Models: A Survey
Shahan et al. Bayesian networks for set-based collaborative design
Behera et al. Large Model-assisted Federated Learning for Object Detection of Autonomous Vehicles in Edge
Chen et al. GenNBV: Generalizable Next-Best-View Policy for Active 3D Reconstruction
Xu et al. GR‐Former: Graph‐reinforcement transformer for skeleton‐based driver action recognition