7 citations · 18 across the 11 of their papers we have counts for
11 papers
MAGE: Multi-scale Autoregressive Generation for Offline Reinforcement Learning
Chenxing Lin, Xinhui Gao, Haipeng Zhang +7
Generative models have gained significant traction in offline reinforcement learning (RL) due to their ability to model complex trajectory distributions. However, existing generati…
OmniEvent: Unified Event Representation Learning
Weiqi Yan, Chenlu Lin, Youbiao Wang +5
Event cameras have gained increasing popularity in computer vision due to their ultra-high dynamic range and temporal resolution. However, event networks heavily rely on task-speci…
A New Adversarial Perspective for LiDAR-based 3D Object Detection
Shijun Zheng, Weiquan Liu, Yu Guo +3
Autonomous vehicles (AVs) rely on LiDAR sensors for environmental perception and decision-making in driving scenarios. However, ensuring the safety and reliability of AVs in comple…
Density-guided Translator Boosts Synthetic-to-Real Unsupervised Domain Adaptive Segmentation of 3D Point Clouds
Zhimin Yuan, Wankang Zeng, Yanfei Su +4
3D synthetic-to-real unsupervised domain adaptive segmentation is crucial to annotating new domains. Self-training is a competitive approach for this task, but its performance is l…
E2PNet: Event to Point Cloud Registration with Spatio-Temporal Representation Learning
Xiuhong Lin, Changjie Qiu, Zhipeng Cai +6
Event cameras have emerged as a promising vision sensor in recent years due to their unparalleled temporal resolution and dynamic range. While registration of 2D RGB images to 3D p…
RiskQ: Risk-sensitive Multi-Agent Reinforcement Learning Value Factorization
Siqi Shen, Chennan Ma, Chao Li +5
Multi-agent systems are characterized by environmental uncertainty, varying policies of agents, and partial observability, which result in significant risks. In the context of Mult…
DSMNet: Deep High-precision 3D Surface Modeling from Sparse Point Cloud Frames
Changjie Qiu, Zhiyong Wang, Xiuhong Lin +3
Existing point cloud modeling datasets primarily express the modeling precision by pose or trajectory precision rather than the point cloud modeling effect itself. Under this deman…
Ins-ATP: Deep Estimation of ATP for Organoid Based on High Throughput Microscopic Images
Xuesheng Bian, Cheng Wang, Shuting Chen +7
Adenosine triphosphate (ATP) is a high-energy phosphate compound and the most direct energy source in organisms. ATP is an essential biomarker for evaluating cell viability in biol…
Interpreting Hidden Semantics in the Intermediate Layers of 3D Point Cloud Classification Neural Network
Weiquan Liu, Minghao Liu, Shijun Zheng +1
Although 3D point cloud classification neural network models have been widely used, the in-depth interpretation of the activation of the neurons and layers is still a challenge. We…
Adaptive Local Adversarial Attacks on 3D Point Clouds for Augmented Reality
Weiquan Liu, Shijun Zheng, Cheng Wang
As the key technology of augmented reality (AR), 3D recognition and tracking are always vulnerable to adversarial examples, which will cause serious security risks to AR systems. A…
DLA-Net: Learning Dual Local Attention Features for Semantic Segmentation of Large-Scale Building Facade Point Clouds
Yanfei Su, Weiquan Liu, Zhimin Yuan +4
Semantic segmentation of building facade is significant in various applications, such as urban building reconstruction and damage assessment. As there is a lack of 3D point clouds…