research
∙
05/29/2019
Volumetric Capture of Humans with a Single RGBD Camera via Semi-Parametric Learning
Volumetric (4D) performance capture is fundamental for AR/VR content gen...
share
research
∙
02/13/2019
DeeperLab: Single-Shot Image Parser
We present a single-shot, bottom-up approach for whole image parsing. Wh...
research
∙
09/11/2018
Searching for Efficient Multi-Scale Architectures for Dense Image Prediction
The design of neural network architectures is an important component for...
research
∙
03/22/2018
PersonLab: Person Pose Estimation and Instance Segmentation with a Bottom-Up, Part-Based, Geometric Embedding Model
We present a box-free bottom-up approach for the tasks of pose estimatio...
research
∙
02/07/2018
Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation
Spatial pyramid pooling module or encode-decoder structure are used in d...
research
∙
12/13/2017
MaskLab: Instance Segmentation by Refining Object Detection with Semantic and Direction Features
In this work, we tackle the problem of instance segmentation, the task o...
research
∙
06/17/2017
Rethinking Atrous Convolution for Semantic Image Segmentation
In this work, we revisit atrous convolution, a powerful tool to explicit...
research
∙
01/06/2017
Towards Accurate Multi-person Pose Estimation in the Wild
We propose a method for multi-person detection and 2-D pose estimation t...
research
∙
06/02/2016
DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs
In this work we address the task of semantic image segmentation with Dee...
research
∙
11/10/2015
Semantic Image Segmentation with Task-Specific Edge Detection Using CNNs and a Discriminatively Trained Domain Transform
Deep convolutional neural networks (CNNs) are the backbone of state-of-a...
research
∙
02/09/2015
Weakly- and Semi-Supervised Learning of a DCNN for Semantic Image Segmentation
Deep convolutional neural networks (DCNNs) trained on a large number of ...
research
∙
12/22/2014
Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs
Deep Convolutional Neural Networks (DCNNs) have recently shown state of ...
research
∙
11/30/2014
Untangling Local and Global Deformations in Deep Convolutional Networks for Image Classification and Sliding Window Detection
Deep Convolutional Neural Networks (DCNNs) commonly use generic `max-poo...
research
∙
06/10/2014
Deep Epitomic Convolutional Neural Networks
Deep convolutional neural networks have recently proven extremely compet...
research
∙
07/22/2011
