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Found 8 papers, 5 papers with code
GAMMA: Graspability-Aware Mobile MAnipulation Policy Learning based on Online Grasping Pose Fusion
Mobile manipulation constitutes a fundamental task for robotic assistants and garners significant attention within the robotics community.
Free Lunch for Gait Recognition: A Novel Relation Descriptor
Gait recognition is to seek correct matches for query individuals by their unique walking patterns.
Learning Gait Representation from Massive Unlabelled Walking Videos: A Benchmark
As far as we know, GaitLU-1M is the first large-scale unlabelled gait dataset, and GaitSSB is the first method that achieves remarkable unsupervised results on the aforementioned benchmarks.
A Comprehensive Survey on Deep Gait Recognition: Algorithms, Datasets and Challenges
We provide a comprehensive survey on recent literature using deep learning and a discussion on the privacy and security of gait biometrics.
Imitation and Adaptation Based on Consistency: A Quadruped Robot Imitates Animals from Videos Using Deep Reinforcement Learning
The deep learning model extracts key points during animal motion from videos.
Real-World Dexterous Object Manipulation based Deep Reinforcement Learning
In this stage, we solved the task of using a real robot to manipulate the cube to a given trajectory.
Graph Stochastic Neural Networks for Semi-supervised Learning
Graph Neural Networks (GNNs) have achieved remarkable performance in the task of the semi-supervised node classification.
RNN-SM: Fast Steganalysis of VoIP Streams Using Recurrent Neural Network
Experiments show that on full embedding rate samples, RNN-SM is of high detection accuracy, which remains over 90% even when the sample is as short as 0. 1 s, and is significantly higher than other state-of-the-art methods.
