13 citations · 17 across the 3 of their papers we have counts for
5 papers
CoCoNets: Continuous Contrastive 3D Scene Representations
Shamit Lal, Mihir Prabhudesai, Ishita Mediratta +2
This paper explores self-supervised learning of amodal 3D feature representations from RGB and RGB-D posed images and videos, agnostic to object and scene semantic content, and eva…
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…
Disentangling 3D Prototypical Networks For Few-Shot Concept Learning
Mihir Prabhudesai, Shamit Lal, Darshan Patil +3
We present neural architectures that disentangle RGB-D images into objects' shapes and styles and a map of the background scene, and explore their applications for few-shot 3D obje…
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…