每天一篇論文 350/365 MVP: Unified Motion and Visual Self-Supervised Learning for Large-Scale Robotic Navig
MVP: Unified Motion and Visual Self-Supervised Learning for Large-Scale Robotic Navigation 核心;基於mvp的方法，使用在大型環境中收集的運動估計和視覺數據進行訓練。MVP方法是通過將局部運動估計與緊湊的視覺表現聯繫起來，從而有效地訓練我們的政策網絡。利用這些數據，強化學習政策可以學會以一種自我監督的方式將運
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相關文章
- 1. 每天一篇論文 296/365 Reinforcement Learning Tracking Control for Robotic Manipulator
- 2. 每天一篇論文 289/365Deep Reinforcement Learning for Robotic Pushing and Picking in Cluttered Environment
- 3. #每天一篇論文 261/365 PointFlowNet: Learning Representations for Rigid Motion Estimation from Point Clouds
- 4. 每天一篇論文 327/365 Instance-wise Depth and Motion Learning from Monocular Videos
- 5. 每天一篇論文 306/365Self-supervised Learning for Single View Depth and Surface Normal Estimation
- 6. 每天一篇論文 291/365 DSNet: Joint Learning for Scene Segmentation and Disparity Estimation
- 7. 每天一篇論文 369/1000 D3VO: Deep Depth, Deep Pose and Deep Uncertainty for Monocular Visual Odometry
- 8. 每天一篇論文 295/365Residual Reinforcement Learning for Robot Control
- 9. /每天一篇論文328/365 Learning Residual Flow as Dynamic Motion from Stereo Videos
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