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Found 11 papers, 8 papers with code
AdaptNet: Policy Adaptation for Physics-Based Character Control
The technique is shown to be effective for adapting existing physics-based controllers to a wide range of new styles for locomotion, new task targets, changes in character morphology and extensive changes in environment.
Composite Motion Learning with Task Control
In contrast to existing data-driven approaches using reinforcement learning that imitate full-body motions, we learn decoupled motions for specific body parts from multiple reference motions simultaneously and directly by leveraging the use of multiple discriminators in a GAN-like setup.
Context-Aware Timewise VAEs for Real-Time Vehicle Trajectory Prediction
Real-time, accurate prediction of human steering behaviors has wide applications, from developing intelligent traffic systems to deploying autonomous driving systems in both real and simulated worlds.
SocialVAE: Human Trajectory Prediction using Timewise Latents
Predicting pedestrian movement is critical for human behavior analysis and also for safe and efficient human-agent interactions.
A GAN-Like Approach for Physics-Based Imitation Learning and Interactive Character Control
We present a simple and intuitive approach for interactive control of physically simulated characters.
Human-Inspired Multi-Agent Navigation using Knowledge Distillation
Despite significant advancements in the field of multi-agent navigation, agents still lack the sophistication and intelligence that humans exhibit in multi-agent settings.
Adaptive Discretization for Continuous Control using Particle Filtering Policy Network
Controlling the movements of highly articulated agents and robots has been a long-standing challenge to model-free deep reinforcement learning.
PFPN: Continuous Control of Physically Simulated Characters using Particle Filtering Policy Network
We exploit particle filtering to dynamically explore and discretize the action space, and track the posterior policy represented as a mixture distribution.
A Multi-oriented Chinese Keyword Spotter Guided by Text Line Detection
Chinese keyword spotting is a challenging task as there is no visual blank for Chinese words.
ICDAR2017 Competition on Reading Chinese Text in the Wild (RCTW-17)
This report introduces RCTW, a new competition that focuses on Chinese text reading.
A Real-time Hand Gesture Recognition and Human-Computer Interaction System
The whole system consists of three components: hand detection, gesture recognition and human-computer interaction (HCI) based on recognition; and realizes the robust control of mouse and keyboard events with a higher accuracy of gesture recognition.
