133 citations · 150 across the 4 of their papers we have counts for
8 papers
HyperDynamics: Meta-Learning Object and Agent Dynamics with Hypernetworks
Zhou Xian, Shamit Lal, Hsiao-Yu Tung +2
We propose HyperDynamics, a dynamics meta-learning framework that conditions on an agent's interactions with the environment and optionally its visual observations, and generates t…
3D-OES: Viewpoint-Invariant Object-Factorized Environment Simulators
Hsiao-Yu Fish Tung, Zhou Xian, Mihir Prabhudesai +2
We propose an action-conditioned dynamics model that predicts scene changes caused by object and agent interactions in a viewpoint-invariant 3D neural scene representation space, i…
3D Object Recognition By Corresponding and Quantizing Neural 3D Scene Representations
Mihir Prabhudesai, Shamit Lal, Hsiao-Yu Fish Tung +3
We propose a system that learns to detect objects and infer their 3D poses in RGB-D images. Many existing systems can identify objects and infer 3D poses, but they heavily rely on…
Learning from Unlabelled Videos Using Contrastive Predictive Neural 3D Mapping
Adam W. Harley, Shrinidhi K. Lakshmikanth, Fangyu Li +3
Predictive coding theories suggest that the brain learns by predicting observations at various levels of abstraction. One of the most basic prediction tasks is view prediction: how…
Learning Spatial Common Sense with Geometry-Aware Recurrent Networks
Hsiao-Yu Fish Tung, Ricson Cheng, Katerina Fragkiadaki
We integrate two powerful ideas, geometry and deep visual representation learning, into recurrent network architectures for mobile visual scene understanding. The proposed networks…
Reward Learning from Narrated Demonstrations
Hsiao-Yu Fish Tung, Adam W. Harley, Liang-Kang Huang +1
Humans effortlessly "program" one another by communicating goals and desires in natural language. In contrast, humans program robotic behaviours by indicating desired object locati…