22 citations · 34 across the 7 of their papers we have counts for
7 papers
Recent Advances of Deep Robotic Affordance Learning: A Reinforcement Learning Perspective
Xintong Yang, Ze Ji, Jing Wu +1
As a popular concept proposed in the field of psychology, affordance has been regarded as one of the important abilities that enable humans to understand and interact with the envi…
MBPTrack: Improving 3D Point Cloud Tracking with Memory Networks and Box Priors
Tian-Xing Xu, Yuan-Chen Guo, Yu-Kun Lai +1
3D single object tracking has been a crucial problem for decades with numerous applications such as autonomous driving. Despite its wide-ranging use, this task remains challenging…
Pose-Controllable 3D Facial Animation Synthesis using Hierarchical Audio-Vertex Attention
Bin Liu, Xiaolin Wei, Bo Li +2
Most of the existing audio-driven 3D facial animation methods suffered from the lack of detailed facial expression and head pose, resulting in unsatisfactory experience of human-ro…
CXTrack: Improving 3D Point Cloud Tracking with Contextual Information
Tian-Xing Xu, Yuan-Chen Guo, Yu-Kun Lai +1
3D single object tracking plays an essential role in many applications, such as autonomous driving. It remains a challenging problem due to the large appearance variation and the s…
Abstract Demonstrations and Adaptive Exploration for Efficient and Stable Multi-step Sparse Reward Reinforcement Learning
Xintong Yang, Ze Ji, Jing Wu +1
Although Deep Reinforcement Learning (DRL) has been popular in many disciplines including robotics, state-of-the-art DRL algorithms still struggle to learn long-horizon, multi-step…
Exploring and Exploiting Hubness Priors for High-Quality GAN Latent Sampling
Yuanbang Liang, Jing Wu, Yu-Kun Lai +1
Despite the extensive studies on Generative Adversarial Networks (GANs), how to reliably sample high-quality images from their latent spaces remains an under-explored topic. In thi…
BBDM: Image-to-image Translation with Brownian Bridge Diffusion Models
Bo Li, Kaitao Xue, Bin Liu +1
Image-to-image translation is an important and challenging problem in computer vision and image processing. Diffusion models (DM) have shown great potentials for high-quality image…