19 citations · 23 across the 6 of their papers we have counts for
6 papers
Closing the Visual Sim-to-Real Gap with Object-Composable NeRFs
Nikhil Mishra, Maximilian Sieb, Pieter Abbeel +1
Deep learning methods for perception are the cornerstone of many robotic systems. Despite their potential for impressive performance, obtaining real-world training data is expensiv…
Convolutional Occupancy Models for Dense Packing of Complex, Novel Objects
Nikhil Mishra, Pieter Abbeel, Xi Chen +1
Dense packing in pick-and-place systems is an important feature in many warehouse and logistics applications. Prior work in this space has largely focused on planning algorithms in…
Autoregressive Uncertainty Modeling for 3D Bounding Box Prediction
YuXuan Liu, Nikhil Mishra, Maximilian Sieb +3
3D bounding boxes are a widespread intermediate representation in many computer vision applications. However, predicting them is a challenging task, largely due to partial observab…
Embodied Language Grounding with 3D Visual Feature Representations
Mihir Prabhudesai, Hsiao-Yu Fish Tung, Syed Ashar Javed +3
We propose associating language utterances to 3D visual abstractions of the scene they describe. The 3D visual abstractions are encoded as 3-dimensional visual feature maps. We inf…
Graph-Structured Visual Imitation
Maximilian Sieb, Zhou Xian, Audrey Huang +2
We cast visual imitation as a visual correspondence problem. Our robotic agent is rewarded when its actions result in better matching of relative spatial configurations for corresp…
Probabilistic Trajectory Segmentation by Means of Hierarchical Dirichlet Process Switching Linear Dynamical Systems
Maximilian Sieb, Matthias Schultheis, Sebastian Szelag +2
Using movement primitive libraries is an effective means to enable robots to solve more complex tasks. In order to build these movement libraries, current algorithms require a prio…