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cs.CV2023
Self-Supervised Instance Segmentation by Grasping
YuXuan Liu, Xi Chen, Pieter Abbeel
Instance segmentation is a fundamental skill for many robotic applications. We propose a self-supervised method that uses grasp interactions to collect segmentation supervision for…
cs.CV2023
Distributional Instance Segmentation: Modeling Uncertainty and High Confidence Predictions with Latent-MaskRCNN
YuXuan Liu, Nikhil Mishra, Pieter Abbeel +1
Object recognition and instance segmentation are fundamental skills in any robotic or autonomous system. Existing state-of-the-art methods are often unable to capture meaningful un…
cs.CV2023
Head-tail Loss: A simple function for Oriented Object Detection and Anchor-free models
Pau Gallés, Xi Chen
This paper presents a new loss function for the prediction of oriented bounding boxes, named head-tail-loss. The loss function consists in minimizing the distance between the predi…