249 citations · 681 across the 14 of their papers we have counts for
15 papers
ShapeMoiré: Channel-Wise Shape-Guided Network for Image Demoiréing
Jinming Cao, Sicheng Shen, Qiu Zhou +3
Photographing optoelectronic displays often introduces unwanted moiré patterns due to analog signal interference between the pixel grids of the display and the camera sensor arrays…
Frame Mining: a Free Lunch for Learning Robotic Manipulation from 3D Point Clouds
Minghua Liu, Xuanlin Li, Zhan Ling +2
We study how choices of input point cloud coordinate frames impact learning of manipulation skills from 3D point clouds. There exist a variety of coordinate frame choices to normal…
ShapeConv: Shape-aware Convolutional Layer for Indoor RGB-D Semantic Segmentation
Jinming Cao, Hanchao Leng, Dani Lischinski +3
RGB-D semantic segmentation has attracted increasing attention over the past few years. Existing methods mostly employ homogeneous convolution operators to consume the RGB and dept…
GSTO: Gated Scale-Transfer Operation for Multi-Scale Feature Learning in Pixel Labeling
Zhuoying Wang, Yongtao Wang, Zhi Tang +4
Existing CNN-based methods for pixel labeling heavily depend on multi-scale features to meet the requirements of both semantic comprehension and detail preservation. State-of-the-a…
DO-Conv: Depthwise Over-parameterized Convolutional Layer
Jinming Cao, Yangyan Li, Mingchao Sun +5
Convolutional layers are the core building blocks of Convolutional Neural Networks (CNNs). In this paper, we propose to augment a convolutional layer with an additional depthwise c…
Face Identity Disentanglement via Latent Space Mapping
Yotam Nitzan, Amit Bermano, Yangyan Li +1
Learning disentangled representations of data is a fundamental problem in artificial intelligence. Specifically, disentangled latent representations allow generative models to cont…