Search Results for author:
Found 21 papers, 8 papers with code
DA$^2$ Dataset: Toward Dexterity-Aware Dual-Arm Grasping
In this paper, we introduce DA$^2$, the first large-scale dual-arm dexterity-aware dataset for the generation of optimal bimanual grasping pairs for arbitrary large objects.
Relative Policy-Transition Optimization for Fast Policy Transfer
Then, integrating the two algorithms offers the complete algorithm Relative Policy-Transition Optimization (RPTO), in which the policy interacts with the two environments simultaneously, such that data collections from two environments, policy and transition updates are completed in one closed loop to form a principled learning framework for policy transfer.
Bootstrapped Hindsight Experience replay with Counterintuitive Prioritization
In this paper, inspired by Bootstrapped DQN, we use multiple heads in DDPG and take advantage of the diversity and uncertainty among multiple heads to improve the data efficiency with relabeled goals.
Superior Performance with Diversified Strategic Control in FPS Games Using General Reinforcement Learning
We provide comprehensive analysis and experiments to elaborate the effect of each component in affecting the agent performance, and demonstrate that the proposed and adopted techniques are important to achieve superior performance in general end-to-end FPS games.
Explainable Hierarchical Imitation Learning for Robotic Drink Pouring
To accurately pour drinks into various containers is an essential skill for service robots.
Self-Supervised Continuous Control without Policy Gradient
Despite the remarkable progress made by the policy gradient algorithms in reinforcement learning (RL), sub-optimal policies usually result from the local exploration property of the policy gradient update.
TStarBot-X: An Open-Sourced and Comprehensive Study for Efficient League Training in StarCraft II Full Game
We show that with orders of less computation scale, a faithful reimplementation of AlphaStar's methods can not succeed and the proposed techniques are necessary to ensure TStarBot-X's competitive performance.
TLeague: A Framework for Competitive Self-Play based Distributed Multi-Agent Reinforcement Learning
This poses non-trivial difficulties for researchers or engineers and prevents the application of MARL to a broader range of real-world problems.
High-Fidelity 3D Digital Human Head Creation from RGB-D Selfies
We present a fully automatic system that can produce high-fidelity, photo-realistic 3D digital human heads with a consumer RGB-D selfie camera.
Joint Hand-object 3D Reconstruction from a Single Image with Cross-branch Feature Fusion
In this work, we propose to consider hand and object jointly in feature space and explore the reciprocity of the two branches.
Curriculum-guided Hindsight Experience Replay
This ``Goal-and-Curiosity-driven Curriculum Learning'' leads to ``Curriculum-guided HER (CHER)'', which adaptively and dynamically controls the exploration-exploitation trade-off during the learning process via hindsight experience selection.
Arena: a toolkit for Multi-Agent Reinforcement Learning
We introduce Arena, a toolkit for multi-agent reinforcement learning (MARL) research.
End-to-End Convolutional Semantic Embeddings
Usually, Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) are employed for learning image and sentence representations, respectively.
Incremental Classifier Learning with Generative Adversarial Networks
To address these problems, we propose (a) a new loss function to combine the cross-entropy loss and distillation loss, (b) a simple way to estimate and remove the unbalance between the old and new classes , and (c) using Generative Adversarial Networks (GANs) to generate historical data and select representative exemplars during generation.
Adversarial Ranking for Language Generation
Rather than training the discriminator to learn and assign absolute binary predicate for individual data sample, the proposed RankGAN is able to analyze and rank a collection of human-written and machine-written sentences by giving a reference group.
Ranked #1 on
Text Generation
on Chinese Poems
Training Deep Networks for Facial Expression Recognition with Crowd-Sourced Label Distribution
Crowd sourcing has become a widely adopted scheme to collect ground truth labels.
Activity Recognition Using A Combination of Category Components And Local Models for Video Surveillance
This paper presents a novel approach for automatic recognition of human activities for video surveillance applications.
Group Event Detection with a Varying Number of Group Members for Video Surveillance
This paper presents a novel approach for automatic recognition of group activities for video surveillance applications.
Deeply-Supervised Nets
Our proposed deeply-supervised nets (DSN) method simultaneously minimizes classification error while making the learning process of hidden layers direct and transparent.
Ranked #23 on
Image Classification
on MNIST
Wide-Baseline Hair Capture Using Strand-Based Refinement
We propose a novel algorithm to reconstruct the 3D geometry of human hairs in wide-baseline setups using strand-based refinement.
Tensor-Based Human Body Modeling
In this paper, we present a novel approach to model 3D human body with variations on both human shape and pose, by exploring a tensor decomposition technique.
