22 citations · 58 across the 12 of their papers we have counts for
12 papers
ACDC: Adaptive Curriculum Planning with Dynamic Contrastive Control for Goal-Conditioned Reinforcement Learning in Robotic Manipulation
Xuerui Wang, Guangyu Ren, Tianhong Dai +4
Goal-conditioned reinforcement learning has shown considerable potential in robotic manipulation; however, existing approaches remain limited by their reliance on prioritizing coll…
Learning to Solve Tasks with Exploring Prior Behaviours
Ruiqi Zhu, Siyuan Li, Tianhong Dai +2
Demonstrations are widely used in Deep Reinforcement Learning (DRL) for facilitating solving tasks with sparse rewards. However, the tasks in real-world scenarios can often have va…
SJ-HD^2R: Selective Joint High Dynamic Range and Denoising Imaging for Dynamic Scenes
Wei Li, Shuai Xiao, Tianhong Dai +4
Ghosting artifacts, motion blur, and low fidelity in highlight are the main challenges in High Dynamic Range (HDR) imaging from multiple Low Dynamic Range (LDR) images. These issue…
NTIRE 2022 Challenge on High Dynamic Range Imaging: Methods and Results
Eduardo Pérez-Pellitero, Sibi Catley-Chandar, Richard Shaw +85
This paper reviews the challenge on constrained high dynamic range (HDR) imaging that was part of the New Trends in Image Restoration and Enhancement (NTIRE) workshop, held in conj…
Diversity-based Trajectory and Goal Selection with Hindsight Experience Replay
Tianhong Dai, Hengyan Liu, Kai Arulkumaran +2
Hindsight experience replay (HER) is a goal relabelling technique typically used with off-policy deep reinforcement learning algorithms to solve goal-oriented tasks; it is well sui…
Wavelet-Based Network For High Dynamic Range Imaging
Tianhong Dai, Wei Li, Xilei Cao +5
High dynamic range (HDR) imaging from multiple low dynamic range (LDR) images has been suffering from ghosting artifacts caused by scene and objects motion. Existing methods, such…
Progressive Multi-scale Fusion Network for RGB-D Salient Object Detection
Guangyu Ren, Yanchu Xie, Tianhong Dai +1
Salient object detection(SOD) aims at locating the most significant object within a given image. In recent years, great progress has been made in applying SOD on many vision tasks.…
Episodic Self-Imitation Learning with Hindsight
Tianhong Dai, Hengyan Liu, Anil Anthony Bharath
Episodic self-imitation learning, a novel self-imitation algorithm with a trajectory selection module and an adaptive loss function, is proposed to speed up reinforcement learning.…
Salient Object Detection Combining a Self-attention Module and a Feature Pyramid Network
Guangyu Ren, Tianhong Dai, Panagiotis Barmpoutis +1
Salient object detection has achieved great improvement by using the Fully Convolution Network (FCN). However, the FCN-based U-shape architecture may cause the dilution problem in…
Coupled Network for Robust Pedestrian Detection with Gated Multi-Layer Feature Extraction and Deformable Occlusion Handling
Tianrui Liu, Wenhan Luo, Lin Ma +3
Pedestrian detection methods have been significantly improved with the development of deep convolutional neural networks. Nevertheless, detecting small-scaled pedestrians and occlu…
Analysing Deep Reinforcement Learning Agents Trained with Domain Randomisation
Tianhong Dai, Kai Arulkumaran, Tamara Gerbert +3
Deep reinforcement learning has the potential to train robots to perform complex tasks in the real world without requiring accurate models of the robot or its environment. A practi…
Gated Multi-layer Convolutional Feature Extraction Network for Robust Pedestrian Detection
Tianrui Liu, Jun-Jie Huang, Tianhong Dai +2
Pedestrian detection methods have been significantly improved with the development of deep convolutional neural networks. Nevertheless, robustly detecting pedestrians with a large…