6.3k citations · 45.8k across the 278 of their papers we have counts for
5 papers · 2 filters
Speed Co-Augmentation for Unsupervised Audio-Visual Pre-training
Jiangliu Wang, Jianbo Jiao, Yibing Song +5
This work aims to improve unsupervised audio-visual pre-training. Inspired by the efficacy of data augmentation in visual contrastive learning, we propose a novel speed co-augmenta…
ALP: Action-Aware Embodied Learning for Perception
Xinran Liang, Anthony Han, Wilson Yan +2
Current methods in training and benchmarking vision models exhibit an over-reliance on passive, curated datasets. Although models trained on these datasets have shown strong perfor…
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…
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…
Where are we in the search for an Artificial Visual Cortex for Embodied Intelligence?
Arjun Majumdar, Karmesh Yadav, Sergio Arnaud +12
We present the largest and most comprehensive empirical study of pre-trained visual representations (PVRs) or visual 'foundation models' for Embodied AI. First, we curate CortexBen…