Camouflaged objects that blend into natural scenes pose significant
chal...
This paper presents our 2nd place solution for the NuPlan Challenge 2023...
In this work, we investigate the potential of improving multi-task train...
Pre-training with offline data and online fine-tuning using reinforcemen...
Recently, Neural architecture search has achieved great success on
class...
The purpose of multi-task reinforcement learning (MTRL) is to train a si...
Transformers exhibit great advantages in handling computer vision tasks....
Maximum entropy (MaxEnt) RL maximizes a combination of the original task...
We consider the safe reinforcement learning (RL) problem of maximizing
u...
Standard model-free reinforcement learning algorithms optimize a policy ...
Travel Time Estimation (TTE) is indispensable in intelligent transportat...
Video creation has been an attractive yet challenging task for artists t...
Recent face reenactment works are limited by the coarse reference landma...
We propose temporally abstract soft actor-critic (TASAC), an off-policy ...
In recent years, neural architecture search (NAS) methods have been prop...
In robot sensing scenarios, instead of passively utilizing human capture...
Deep neural networks (DNNs) have achieved remarkable success in computer...
We introduce a feature scattering-based adversarial training approach fo...
Conventional adversarial training methods using attacks that manipulate ...
Object detection is an important vision task and has emerged as an
indis...
Sequence-to-sequence models are commonly trained via maximum likelihood
...
Generative adversarial networks (GANs) have achieved significant success...
Recently there has been a rising interest in training agents, embodied i...
Building intelligent agents that can communicate with and learn from hum...
We build a virtual agent for learning language in a 2D maze-like world. ...
Visual recognition under adverse conditions is a very important and
chal...
One of the long-term goals of artificial intelligence is to build an age...
We tackle a task where an agent learns to navigate in a 2D maze-like
env...
Typical blur from camera shake often deviates from the standard uniform
...
Blind deconvolution involves the estimation of a sharp signal or image g...
Image super-resolution (SR) is one of the long-standing and active topic...