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Found 8 papers, 5 papers with code
PaddingFlow: Improving Normalizing Flows with Padding-Dimensional Noise
To implement PaddingFlow, only the dimension of normalizing flows needs to be modified.
Ranked #1 on
Density Estimation
on MNIST
(MMD-L2 metric)
PPNet: A Two-Stage Neural Network for End-to-end Path Planning
The results show that PPNet can find a near-optimal solution in 15. 3ms, which is much shorter than the state-of-the-art path planners.
Deep Reinforcement Learning Based on Local GNN for Goal-conditioned Deformable Object Rearranging
Some research has been attempting to design a general framework to obtain more advanced manipulation capabilities for deformable rearranging tasks, with lots of progress achieved in simulation.
Graph-Transporter: A Graph-based Learning Method for Goal-Conditioned Deformable Object Rearranging Task
Rearranging deformable objects is a long-standing challenge in robotic manipulation for the high dimensionality of configuration space and the complex dynamics of deformable objects.
Foldsformer: Learning Sequential Multi-Step Cloth Manipulation With Space-Time Attention
Foldformer can complete multi-step cloth manipulation tasks even when configurations of the cloth (e. g., size and pose) vary from configurations in the general demonstrations.
Visual-tactile Fusion for Transparent Object Grasping in Complex Backgrounds
Here, a visual-tactile fusion framework for transparent object grasping under complex backgrounds and variant light conditions is proposed, including the grasping position detection, tactile calibration, and visual-tactile fusion based classification.
Polarimetric Inverse Rendering for Transparent Shapes Reconstruction
We build a polarization dataset for multi-view transparent shapes reconstruction to verify our method.
Transparent Shape from a Single View Polarization Image
To train and test our method, we construct a dataset for transparent shape from polarization with paired polarization images and ground-truth normal maps.
