In recent years, data-driven reinforcement learning (RL), also known as
...
This work proposes a novel face-swapping framework FlowFace++, utilizing...
For few-shot learning, it is still a critical challenge to realize
photo...
Recent popular Role-Playing Games (RPGs) saw the great success of charac...
Real-world cooperation often requires intensive coordination among agent...
Recent advances in multi-agent reinforcement learning (MARL) allow agent...
Determining causal effects of temporal multi-intervention assists
decisi...
As a fine-grained and local expression behavior measurement, facial acti...
Unsupervised reinforcement learning (URL) poses a promising paradigm to ...
Developing a safe, stable, and efficient obstacle avoidance policy in cr...
We investigate model-free multi-agent reinforcement learning (MARL) in
e...
Since 2017, the Transformer-based models play critical roles in various
...
Recently, a variety of neural models have been proposed for lyrics
gener...
Reinforcement learning based recommender systems (RL-based RS) aims at
l...
Standard multi-task benchmarks are essential for driving the progress of...
While deep reinforcement learning has achieved promising results in
chal...
We propose an audio-driven talking-head method to generate photo-realist...
Graphically-rich applications such as games are ubiquitous with attracti...
Generating long and coherent text is an important but challenging task,
...
Automatic metrics are essential for developing natural language generati...
The ultra-large-scale pre-training model can effectively improve the eff...
In this paper, we propose a novel text-based talking-head video generati...
In business domains, bundling is one of the most important marketing
str...
In recent years, there are great interests as well as challenges in appl...
The development of deep reinforcement learning (DRL) has benefited from ...
This paper presents GraphFederator, a novel approach to construct joint
...
Game character customization is one of the core features of many recent
...
With the rapid development of Role-Playing Games (RPGs), players are now...
Meta reinforcement learning (meta-RL) provides a principled approach for...
The automatic intensity estimation of facial action units (AUs) from a s...
Exploration is a key problem in reinforcement learning. Recently bonus-b...
Transfer Learning (TL) has shown great potential to accelerate Reinforce...
Recently, deep multiagent reinforcement learning (MARL) has become a hig...
This paper describes an approach to the facial action units detections. ...
Facial Action Units Detection (FAUD), one of the main approaches for fac...
Designing artificial intelligence for games (Game AI) has been long
reco...
A lot of efforts have been devoted to investigating how agents can learn...
Despite achieving great success on performance in various sequential dec...
Character customization system is an important component in Role-Playing...
In multiagent systems (MASs), each agent makes individual decisions but ...
Experience reuse is key to sample-efficient reinforcement learning. One ...
Recent face reenactment studies have achieved remarkable success either
...
Deep Reinforcement Learning (DRL) has been applied to address a variety ...
Despite deep reinforcement learning has recently achieved great successe...