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Found 6 papers, 0 papers with code
Large-scale Weakly Supervised Learning for Road Extraction from Satellite Imagery
Our extensive experimental results show that the prediction accuracy increases with the amount of the weakly labeled data, as well as the road density in the areas chosen for training.
T2IAT: Measuring Valence and Stereotypical Biases in Text-to-Image Generation
In this work, we seek to measure more complex human biases exist in the task of text-to-image generations.
Navigation as Attackers Wish? Towards Building Robust Embodied Agents under Federated Learning
However, since the local data is inaccessible to the server under federated learning, attackers may easily poison the training data of the local client to build a backdoor in the agent without notice.
JARVIS: A Neuro-Symbolic Commonsense Reasoning Framework for Conversational Embodied Agents
Building a conversational embodied agent to execute real-life tasks has been a long-standing yet quite challenging research goal, as it requires effective human-agent communication, multi-modal understanding, long-range sequential decision making, etc.
Test-Time Personalization with a Transformer for Human Pose Estimation
During test time, we personalize and adapt our model by fine-tuning with the self-supervised objective.
Leveraging Crowdsourced GPS Data for Road Extraction from Aerial Imagery
Deep learning is revolutionizing the mapping industry.
