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10/14/2022
Frame Mining: a Free Lunch for Learning Robotic Manipulation from 3D Point Clouds
We study how choices of input point cloud coordinate frames impact learn...
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08/24/2021
ShapeConv: Shape-aware Convolutional Layer for Indoor RGB-D Semantic Segmentation
RGB-D semantic segmentation has attracted increasing attention over the ...
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06/22/2020
DO-Conv: Depthwise Over-parameterized Convolutional Layer
Convolutional layers are the core building blocks of Convolutional Neura...
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05/27/2020
GSTO: Gated Scale-Transfer Operation for Multi-Scale Feature Learning in Pixel Labeling
Existing CNN-based methods for pixel labeling heavily depend on multi-sc...
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05/15/2020
Face Identity Disentanglement via Latent Space Mapping
Learning disentangled representations of data is a fundamental problem i...
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01/19/2020
MixTConv: Mixed Temporal Convolutional Kernels for Efficient Action Recogntion
To efficiently extract spatiotemporal features of video for action recog...
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05/21/2018
DiDA: Disentangled Synthesis for Domain Adaptation
Unsupervised domain adaptation aims at learning a shared model for two r...
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01/23/2018
PointCNN: Convolution On X-Transformed Points
We present a simple and general framework for feature learning from poin...
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01/23/2018
PointCNN
We present a simple and general framework for feature learning from poin...
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10/17/2017
Large-Scale 3D Shape Reconstruction and Segmentation from ShapeNet Core55
We introduce a large-scale 3D shape understanding benchmark using data a...
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03/29/2017
Bundle Optimization for Multi-aspect Embedding
Understanding semantic similarity among images is the core of a wide ran...
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08/18/2016
A Holistic Approach for Data-Driven Object Cutout
Object cutout is a fundamental operation for image editing and manipulat...
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05/20/2016
FPNN: Field Probing Neural Networks for 3D Data
Building discriminative representations for 3D data has been an importan...
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04/10/2016