Search Results for author:
Found 9 papers, 5 papers with code
Rethinking Optimization with Differentiable Simulation from a Global Perspective
In this work, we study the challenges that differentiable simulation presents when it is not feasible to expect that a single descent reaches a global optimum, which is often a problem in contact-rich scenarios.
AutoLay: Benchmarking amodal layout estimation for autonomous driving
Given an image or a video captured from a monocular camera, amodal layout estimation is the task of predicting semantics and occupancy in bird's eye view.
gradSim: Differentiable simulation for system identification and visuomotor control
We consider the problem of estimating an object's physical properties such as mass, friction, and elasticity directly from video sequences.
DRACO: Weakly Supervised Dense Reconstruction And Canonicalization of Objects
We present DRACO, a method for Dense Reconstruction And Canonicalization of Object shape from one or more RGB images.
RobustPointSet: A Dataset for Benchmarking Robustness of Point Cloud Classifiers
We also find that robustness to unseen transformations cannot be brought about merely by extensive data augmentation.
MonoLayout: Amodal scene layout from a single image
We dub this problem amodal scene layout estimation, which involves "hallucinating" scene layout for even parts of the world that are occluded in the image.
Multi-object Monocular SLAM for Dynamic Environments
In this paper, we tackle the problem of multibody SLAM from a monocular camera.
Kaolin: A PyTorch Library for Accelerating 3D Deep Learning Research
We present Kaolin, a PyTorch library aiming to accelerate 3D deep learning research.
gradSLAM: Automagically differentiable SLAM
Blending representation learning approaches with simultaneous localization and mapping (SLAM) systems is an open question, because of their highly modular and complex nature.
Representation Learning
Simultaneous Localization and Mapping
