237 citations · 1.2k across the 68 of their papers we have counts for
17 papers · 1 filter
Learning to Reconstruct Shapes from Unseen Classes
Xiuming Zhang, Zhoutong Zhang, Chengkai Zhang +3
From a single image, humans are able to perceive the full 3D shape of an object by exploiting learned shape priors from everyday life. Contemporary single-image 3D reconstruction a…
Visual Object Networks: Image Generation with Disentangled 3D Representation
Jun-Yan Zhu, Zhoutong Zhang, Chengkai Zhang +4
Recent progress in deep generative models has led to tremendous breakthroughs in image generation. However, while existing models can synthesize photorealistic images, they lack an…
ChainQueen: A Real-Time Differentiable Physical Simulator for Soft Robotics
Yuanming Hu, Jiancheng Liu, Andrew Spielberg +5
Physical simulators have been widely used in robot planning and control. Among them, differentiable simulators are particularly favored, as they can be incorporated into gradient-b…
Neural-Symbolic VQA: Disentangling Reasoning from Vision and Language Understanding
Kexin Yi, Jiajun Wu, Chuang Gan +3
We marry two powerful ideas: deep representation learning for visual recognition and language understanding, and symbolic program execution for reasoning. Our neural-symbolic visua…
Learning Particle Dynamics for Manipulating Rigid Bodies, Deformable Objects, and Fluids
Yunzhu Li, Jiajun Wu, Russ Tedrake +2
Real-life control tasks involve matters of various substances---rigid or soft bodies, liquid, gas---each with distinct physical behaviors. This poses challenges to traditional rigi…
Physical Primitive Decomposition
Zhijian Liu, William T. Freeman, Joshua B. Tenenbaum +1
Objects are made of parts, each with distinct geometry, physics, functionality, and affordances. Developing such a distributed, physical, interpretable representation of objects wi…