237 citations · 559 across the 5 of their papers we have counts for
6 papers
DensePhysNet: Learning Dense Physical Object Representations via Multi-step Dynamic Interactions
Zhenjia Xu, Jiajun Wu, Andy Zeng +2
We study the problem of learning physical object representations for robot manipulation. Understanding object physics is critical for successful object manipulation, but also chall…
The Neuro-Symbolic Concept Learner: Interpreting Scenes, Words, and Sentences From Natural Supervision
Jiayuan Mao, Chuang Gan, Pushmeet Kohli +2
We propose the Neuro-Symbolic Concept Learner (NS-CL), a model that learns visual concepts, words, and semantic parsing of sentences without explicit supervision on any of them; in…
Learning Sight from Sound: Ambient Sound Provides Supervision for Visual Learning
Andrew Owens, Jiajun Wu, Josh H. McDermott +2
The sound of crashing waves, the roar of fast-moving cars -- sound conveys important information about the objects in our surroundings. In this work, we show that ambient sounds ca…
Attention Clusters: Purely Attention Based Local Feature Integration for Video Classification
Xiang Long, Chuang Gan, Gerard de Melo +3
Recently, substantial research effort has focused on how to apply CNNs or RNNs to better extract temporal patterns from videos, so as to improve the accuracy of video classificatio…
MarrNet: 3D Shape Reconstruction via 2.5D Sketches
Jiajun Wu, Yifan Wang, Tianfan Xue +3
3D object reconstruction from a single image is a highly under-determined problem, requiring strong prior knowledge of plausible 3D shapes. This introduces challenges for learning-…
Visual Dynamics: Probabilistic Future Frame Synthesis via Cross Convolutional Networks
Tianfan Xue, Jiajun Wu, Katherine L. Bouman +1
We study the problem of synthesizing a number of likely future frames from a single input image. In contrast to traditional methods, which have tackled this problem in a determinis…