activity
20182020
most citedRethinking Sampling in 3D Point Cloud Generative Adversarial Networks

14 citations · 23 across the 5 of their papers we have counts for

collaborators

10 papers

cs.CV20205 cited

Object-Centric Multi-View Aggregation

Shubham Tulsiani, Or Litany, Charles R. Qi +2

We present an approach for aggregating a sparse set of views of an object in order to compute a semi-implicit 3D representation in the form of a volumetric feature grid. Key to our…

cs.CV202014 cited

Rethinking Sampling in 3D Point Cloud Generative Adversarial Networks

He Wang, Zetian Jiang, Li Yi +3

In this paper, we examine the long-neglected yet important effects of point sampling patterns in point cloud GANs. Through extensive experiments, we show that sampling-insensitive…

cs.CV2020

SAPIEN: A SimulAted Part-based Interactive ENvironment

Fanbo Xiang, Yuzhe Qin, Kaichun Mo +11

Building home assistant robots has long been a pursuit for vision and robotics researchers. To achieve this task, a simulated environment with physically realistic simulation, suff…

cs.CV2020

PT2PC: Learning to Generate 3D Point Cloud Shapes from Part Tree Conditions

Kaichun Mo, He Wang, Xinchen Yan +1

3D generative shape modeling is a fundamental research area in computer vision and interactive computer graphics, with many real-world applications. This paper investigates the nov…

cs.CV2020

Curriculum DeepSDF

Yueqi Duan, Haidong Zhu, He Wang +3

When learning to sketch, beginners start with simple and flexible shapes, and then gradually strive for more complex and accurate ones in the subsequent training sessions. In this…

cs.CV20201 cited

Predicting the Physical Dynamics of Unseen 3D Objects

Davis Rempe, Srinath Sridhar, He Wang +1

Machines that can predict the effect of physical interactions on the dynamics of previously unseen object instances are important for creating better robots and interactive virtual…