133 citations · 161 across the 8 of their papers we have counts for
10 papers · 1 filter
3D View Prediction Models of the Dorsal Visual Stream
Gabriel Sarch, Hsiao-Yu Fish Tung, Aria Wang +2
Deep neural network representations align well with brain activity in the ventral visual stream. However, the primate visual system has a distinct dorsal processing stream with dif…
Physion++: Evaluating Physical Scene Understanding that Requires Online Inference of Different Physical Properties
Hsiao-Yu Tung, Mingyu Ding, Zhenfang Chen +6
General physical scene understanding requires more than simply localizing and recognizing objects -- it requires knowledge that objects can have different latent properties (e.g.,…
3D-IntPhys: Towards More Generalized 3D-grounded Visual Intuitive Physics under Challenging Scenes
Haotian Xue, Antonio Torralba, Joshua B. Tenenbaum +3
Given a visual scene, humans have strong intuitions about how a scene can evolve over time under given actions. The intuition, often termed visual intuitive physics, is a critical…
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…
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…