ECCV 2018

Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation

ECCV 2018 tensorflow/models

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.

IMAGE CLASSIFICATION LESION SEGMENTATION SEMANTIC SEGMENTATION

Progressive Neural Architecture Search

ECCV 2018 tensorflow/models

We propose a new method for learning the structure of convolutional neural networks (CNNs) that is more efficient than recent state-of-the-art methods based on reinforcement learning and evolutionary algorithms.

IMAGE CLASSIFICATION NEURAL ARCHITECTURE SEARCH

Group Normalization

ECCV 2018 facebookresearch/detectron

FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet.

OBJECT DETECTION VIDEO CLASSIFICATION

A Closed-form Solution to Photorealistic Image Stylization

ECCV 2018 NVIDIA/FastPhotoStyle

Photorealistic image stylization concerns transferring style of a reference photo to a content photo with the constraint that the stylized photo should remain photorealistic.

IMAGE STYLIZATION

Wasserstein Divergence for GANs

ECCV 2018 eriklindernoren/PyTorch-GAN

In many domains of computer vision, generative adversarial networks (GANs) have achieved great success, among which the fam- ily of Wasserstein GANs (WGANs) is considered to be state-of-the-art due to the theoretical contributions and competitive qualitative performance.

IMAGE GENERATION

Joint 3D Face Reconstruction and Dense Alignment with Position Map Regression Network

ECCV 2018 YadiraF/PRNet

We propose a straightforward method that simultaneously reconstructs the 3D facial structure and provides dense alignment.

3D FACE RECONSTRUCTION FACE ALIGNMENT

Unified Perceptual Parsing for Scene Understanding

ECCV 2018 CSAILVision/semantic-segmentation-pytorch

In this paper, we study a new task called Unified Perceptual Parsing, which requires the machine vision systems to recognize as many visual concepts as possible from a given image.

SCENE UNDERSTANDING SEMANTIC SEGMENTATION

AMC: AutoML for Model Compression and Acceleration on Mobile Devices

ECCV 2018 NervanaSystems/distiller

Model compression is a critical technique to efficiently deploy neural network models on mobile devices which have limited computation resources and tight power budgets.

MODEL COMPRESSION NEURAL ARCHITECTURE SEARCH