CVPR 2017

Pyramid Scene Parsing Network

CVPR 2017 tensorflow/models

Scene parsing is challenging for unrestricted open vocabulary and diverse scenes.

REAL-TIME SEMANTIC SEGMENTATION SCENE PARSING

Cognitive Mapping and Planning for Visual Navigation

CVPR 2017 tensorflow/models

The accumulated belief of the world enables the agent to track visited regions of the environment.

VISUAL NAVIGATION

Unsupervised Pixel-Level Domain Adaptation with Generative Adversarial Networks

CVPR 2017 tensorflow/models

Collecting well-annotated image datasets to train modern machine learning algorithms is prohibitively expensive for many tasks.

UNSUPERVISED DOMAIN ADAPTATION

Full Resolution Image Compression with Recurrent Neural Networks

CVPR 2017 tensorflow/models

As far as we know, this is the first neural network architecture that is able to outperform JPEG at image compression across most bitrates on the rate-distortion curve on the Kodak dataset images, with and without the aid of entropy coding.

IMAGE COMPRESSION

Speed/accuracy trade-offs for modern convolutional object detectors

CVPR 2017 tensorflow/models

The goal of this paper is to serve as a guide for selecting a detection architecture that achieves the right speed/memory/accuracy balance for a given application and platform.

OBJECT DETECTION

Learning from Simulated and Unsupervised Images through Adversarial Training

CVPR 2017 tensorflow/models

With recent progress in graphics, it has become more tractable to train models on synthetic images, potentially avoiding the need for expensive annotations.

GAZE ESTIMATION HAND POSE ESTIMATION IMAGE-TO-IMAGE TRANSLATION

Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network

CVPR 2017 tensorflow/models

The adversarial loss pushes our solution to the natural image manifold using a discriminator network that is trained to differentiate between the super-resolved images and original photo-realistic images.

IMAGE SUPER-RESOLUTION

Feature Pyramid Networks for Object Detection

CVPR 2017 facebookresearch/detectron

Feature pyramids are a basic component in recognition systems for detecting objects at different scales.

OBJECT DETECTION