activity
20182023
most citedExtending Adversarial Attacks and Defenses to Deep 3D Point Cloud Classifiers

18 citations · 85 across the 17 of their papers we have counts for

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Showing 2020Show all

9 papers · 1 filter

cs.CV2020

Semantically Robust Unpaired Image Translation for Data with Unmatched Semantics Statistics

Zhiwei Jia, Bodi Yuan, Kangkang Wang +4

Many applications of unpaired image-to-image translation require the input contents to be preserved semantically during translations. Unaware of the inherently unmatched semantics…

cs.CV20207 cited

Compositionally Generalizable 3D Structure Prediction

Songfang Han, Jiayuan Gu, Kaichun Mo +4

Single-image 3D shape reconstruction is an important and long-standing problem in computer vision. A plethora of existing works is constantly pushing the state-of-the-art performan…

cs.CV20205 cited

Refactoring Policy for Compositional Generalizability using Self-Supervised Object Proposals

Tongzhou Mu, Jiayuan Gu, Zhiwei Jia +2

We study how to learn a policy with compositional generalizability. We propose a two-stage framework, which refactorizes a high-reward teacher policy into a generalizable student p…

cs.LG20203 cited

Towards Scale-Invariant Graph-related Problem Solving by Iterative Homogeneous Graph Neural Networks

Hao Tang, Zhiao Huang, Jiayuan Gu +2

Current graph neural networks (GNNs) lack generalizability with respect to scales (graph sizes, graph diameters, edge weights, etc..) when solving many graph analysis problems. Tak…

cs.GR2020

Photon-Driven Neural Path Guiding

Shilin Zhu, Zexiang Xu, Tiancheng Sun +5

Although Monte Carlo path tracing is a simple and effective algorithm to synthesize photo-realistic images, it is often very slow to converge to noise-free results when involving c…

cs.CV20205 cited

Weakly-supervised 3D Shape Completion in the Wild

Jiayuan Gu, Wei-Chiu Ma, Sivabalan Manivasagam +5

3D shape completion for real data is important but challenging, since partial point clouds acquired by real-world sensors are usually sparse, noisy and unaligned. Different from pr…