343 citations · 499 across the 15 of their papers we have counts for
8 papers · 1 filter
Causal Deep Reinforcement Learning Using Observational Data
Wenxuan Zhu, Chao Yu, Qiang Zhang
Deep reinforcement learning (DRL) requires the collection of interventional data, which is sometimes expensive and even unethical in the real world, such as in the autonomous drivi…
Multi-Camera Calibration Free BEV Representation for 3D Object Detection
Hongxiang Jiang, Wenming Meng, Hongmei Zhu +2
In advanced paradigms of autonomous driving, learning Bird's Eye View (BEV) representation from surrounding views is crucial for multi-task framework. However, existing methods bas…
Improving Visual-Semantic Embedding with Adaptive Pooling and Optimization Objective
Zijian Zhang, Chang Shu, Ya Xiao +7
Visual-Semantic Embedding (VSE) aims to learn an embedding space where related visual and semantic instances are close to each other. Recent VSE models tend to design complex struc…
Relay Hindsight Experience Replay: Self-Guided Continual Reinforcement Learning for Sequential Object Manipulation Tasks with Sparse Rewards
Yongle Luo, Yuxin Wang, Kun Dong +4
Exploration with sparse rewards remains a challenging research problem in reinforcement learning (RL). Especially for sequential object manipulation tasks, the RL agent always rece…
Learning Dynamic View Synthesis With Few RGBD Cameras
Shengze Wang, YoungJoong Kwon, Yuan Shen +4
There have been significant advancements in dynamic novel view synthesis in recent years. However, current deep learning models often require (1) prior models (e.g., SMPL human mod…
Nonperturbative Determination of Collins-Soper Kernel from Quasi Transverse-Momentum Dependent Wave Functions
Min-Huan Chu, Zhi-Fu Deng, Jun Hua +10
In the framework of large-momentum effective theory at one-loop matching accuracy, we perform a lattice calculation of the Collins-Soper kernel which governs the rapidity evolution…