Search Results

Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation

tensorflow/models ECCV 2018

The former networks are able to encode multi-scale contextual information by probing the incoming features with filters or pooling operations at multiple rates and multiple effective fields-of-view, while the latter networks can capture sharper object boundaries by gradually recovering the spatial information.

 Ranked #1 on Semantic Segmentation on PASCAL VOC 2012 test (using extra training data)

Image Classification Image Segmentation +2

Meta-Learning Update Rules for Unsupervised Representation Learning

tensorflow/models ICLR 2019

Specifically, we target semi-supervised classification performance, and we meta-learn an algorithm -- an unsupervised weight update rule -- that produces representations useful for this task.

Meta-Learning Representation Learning

Unifying Deep Local and Global Features for Image Search

tensorflow/models ECCV 2020

Image retrieval is the problem of searching an image database for items that are similar to a query image.

Dimensionality Reduction Image Retrieval +1

Time-Contrastive Networks: Self-Supervised Learning from Video

tensorflow/models 23 Apr 2017

While representations are learned from an unlabeled collection of task-related videos, robot behaviors such as pouring are learned by watching a single 3rd-person demonstration by a human.

Metric Learning reinforcement-learning +3

Deep Residual Learning for Image Recognition

tensorflow/models CVPR 2016

Deep residual nets are foundations of our submissions to ILSVRC & COCO 2015 competitions, where we also won the 1st places on the tasks of ImageNet detection, ImageNet localization, COCO detection, and COCO segmentation.

Domain Generalization +11

Going Deeper with Convolutions

tensorflow/models CVPR 2015

We propose a deep convolutional neural network architecture codenamed "Inception", which was responsible for setting the new state of the art for classification and detection in the ImageNet Large-Scale Visual Recognition Challenge 2014 (ILSVRC 2014).

General Classification Image Classification +2

Learning Transferable Architectures for Scalable Image Recognition

tensorflow/models CVPR 2018

In our experiments, we search for the best convolutional layer (or "cell") on the CIFAR-10 dataset and then apply this cell to the ImageNet dataset by stacking together more copies of this cell, each with their own parameters to design a convolutional architecture, named "NASNet architecture".

Classification Image Classification +1

Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

tensorflow/models 11 Feb 2015

Training Deep Neural Networks is complicated by the fact that the distribution of each layer's inputs changes during training, as the parameters of the previous layers change.

Ranked #487 on Image Classification on ImageNet (Number of params metric)

General Classification Image Classification