10 citations · 20 across the 7 of their papers we have counts for
7 papers
Generative Category-Level Shape and Pose Estimation with Semantic Primitives
Guanglin Li, Yifeng Li, Zhichao Ye +4
Empowering autonomous agents with 3D understanding for daily objects is a grand challenge in robotics applications. When exploring in an unknown environment, existing methods for o…
Generative Enriched Sequential Learning (ESL) Approach for Molecular Design via Augmented Domain Knowledge
Mohammad Sajjad Ghaemi, Karl Grantham, Isaac Tamblyn +2
Deploying generative machine learning techniques to generate novel chemical structures based on molecular fingerprint representation has been well established in molecular design.…
Simultaneous Semantic and Collision Learning for 6-DoF Grasp Pose Estimation
Yiming Li, Tao Kong, Ruihang Chu +3
Grasping in cluttered scenes has always been a great challenge for robots, due to the requirement of the ability to well understand the scene and object information. Previous works…
Learning to Design and Construct Bridge without Blueprint
Yunfei Li, Tao Kong, Lei Li +2
Autonomous assembly has been a desired functionality of many intelligent robot systems. We study a new challenging assembly task, designing and constructing a bridge without a blue…
Deep Evolutionary Learning for Molecular Design
Yifeng Li, Hsu Kiang Ooi, Alain Tchagang
In this paper, we propose a deep evolutionary learning (DEL) process that integrates fragment-based deep generative model and multi-objective evolutionary computation for molecular…
Exploring Deep Anomaly Detection Methods Based on Capsule Net
Xiaoyan Li, Iluju Kiringa, Tet Yeap +2
In this paper, we develop and explore deep anomaly detection techniques based on the capsule network (CapsNet) for image data. Being able to encoding intrinsic spatial relationship…
Defending Adversarial Attacks by Correcting logits
Yifeng Li, Lingxi Xie, Ya Zhang +3
Generating and eliminating adversarial examples has been an intriguing topic in the field of deep learning. While previous research verified that adversarial attacks are often frag…