7 citations · 14 across the 13 of their papers we have counts for
14 papers
GlobalSplat: Efficient Feed-Forward 3D Gaussian Splatting via Global Scene Tokens
Roni Itkin, Noam Issachar, Yehonatan Keypur +3
The efficient spatial allocation of primitives serves as the foundation of 3D Gaussian Splatting, as it directly dictates the synergy between representation compactness, reconstruc…
Bridging Simulation and Reality: Cross-Domain Transfer with Semantic 2D Gaussian Splatting
Jian Tang, Pu Pang, Haowen Sun +4
Cross-domain transfer in robotic manipulation remains a longstanding challenge due to the significant domain gap between simulated and real-world environments. Existing methods suc…
PRISM: Projection-based Reward Integration for Scene-Aware Real-to-Sim-to-Real Transfer with Few Demonstrations
Haowen Sun, Han Wang, Chengzhong Ma +4
Learning from few demonstrations to develop policies robust to variations in robot initial positions and object poses is a problem of significant practical interest in robotics. Co…
REGNet V2: End-to-End REgion-based Grasp Detection Network for Grippers of Different Sizes in Point Clouds
Binglei Zhao, Han Wang, Jian Tang +5
Grasping has been a crucial but challenging problem in robotics for many years. One of the most important challenges is how to make grasping generalizable and robust to novel objec…
Grounded Answers for Multi-agent Decision-making Problem through Generative World Model
Zeyang Liu, Xinrui Yang, Shiguang Sun +4
Recent progress in generative models has stimulated significant innovations in many fields, such as image generation and chatbots. Despite their success, these models often produce…
Imagine, Initialize, and Explore: An Effective Exploration Method in Multi-Agent Reinforcement Learning
Zeyang Liu, Lipeng Wan, Xinrui Yang +3
Effective exploration is crucial to discovering optimal strategies for multi-agent reinforcement learning (MARL) in complex coordination tasks. Existing methods mainly utilize intr…
ESMC: Entire Space Multi-Task Model for Post-Click Conversion Rate via Parameter Constraint
Zhenhao Jiang, Biao Zeng, Hao Feng +7
Large-scale online recommender system spreads all over the Internet being in charge of two basic tasks: Click-Through Rate (CTR) and Post-Click Conversion Rate (CVR) estimations. H…
MMRDN: Consistent Representation for Multi-View Manipulation Relationship Detection in Object-Stacked Scenes
Han Wang, Jiayuan Zhang, Lipeng Wan +3
Manipulation relationship detection (MRD) aims to guide the robot to grasp objects in the right order, which is important to ensure the safety and reliability of grasping in object…
Prioritized Planning for Target-Oriented Manipulation via Hierarchical Stacking Relationship Prediction
Zewen Wu, Jian Tang, Xingyu Chen +3
In scenarios involving the grasping of multiple targets, the learning of stacking relationships between objects is fundamental for robots to execute safely and efficiently. However…
Greedy based Value Representation for Optimal Coordination in Multi-agent Reinforcement Learning
Lipeng Wan, Zeyang Liu, Xingyu Chen +2
Due to the representation limitation of the joint Q value function, multi-agent reinforcement learning methods with linear value decomposition (LVD) or monotonic value decompositio…
Greedy-based Value Representation for Optimal Coordination in Multi-agent Reinforcement Learning
Lipeng Wan, Zeyang Liu, Xingyu Chen +2
Due to the representation limitation of the joint Q value function, multi-agent reinforcement learning methods with linear value decomposition (LVD) or monotonic value decompositio…
MBDF-Net: Multi-Branch Deep Fusion Network for 3D Object Detection
Xun Tan, Xingyu Chen, Guowei Zhang +2
Point clouds and images could provide complementary information when representing 3D objects. Fusing the two kinds of data usually helps to improve the detection results. However,…
Probabilistic Human Motion Prediction via A Bayesian Neural Network
Jie Xu, Xingyu Chen, Xuguang Lan +1
Human motion prediction is an important and challenging topic that has promising prospects in efficient and safe human-robot-interaction systems. Currently, the majority of the hum…
A Boundary Based Out-of-Distribution Classifier for Generalized Zero-Shot Learning
Xingyu Chen, Xuguang Lan, Fuchun Sun +1
Generalized Zero-Shot Learning (GZSL) is a challenging topic that has promising prospects in many realistic scenarios. Using a gating mechanism that discriminates the unseen sample…