ICCV 2019

Searching for MobileNetV3

ICCV 2019 tensorflow/models

We achieve new state of the art results for mobile classification, detection and segmentation.

IMAGE CLASSIFICATION NEURAL ARCHITECTURE SEARCH OBJECT DETECTION SEMANTIC SEGMENTATION

An Empirical Study of Spatial Attention Mechanisms in Deep Networks

ICCV 2019 open-mmlab/mmdetection

Attention mechanisms have become a popular component in deep neural networks, yet there has been little examination of how different influencing factors and methods for computing attention from these factors affect performance.

Scale-Aware Trident Networks for Object Detection

ICCV 2019 facebookresearch/detectron2

In this work, we first present a controlled experiment to investigate the effect of receptive fields for scale variation in object detection.

OBJECT DETECTION

Depth from Videos in the Wild: Unsupervised Monocular Depth Learning from Unknown Cameras

ICCV 2019 google-research/google-research

We present a novel method for simultaneous learning of depth, egomotion, object motion, and camera intrinsics from monocular videos, using only consistency across neighboring video frames as supervision signal.

DEPTH ESTIMATION

Rethinking ImageNet Pre-training

ICCV 2019 tensorpack/tensorpack

We report competitive results on object detection and instance segmentation on the COCO dataset using standard models trained from random initialization.

INSTANCE SEGMENTATION OBJECT DETECTION SEMANTIC SEGMENTATION

SC-FEGAN: Face Editing Generative Adversarial Network with User's Sketch and Color

ICCV 2019 run-youngjoo/SC-FEGAN

We present a novel image editing system that generates images as the user provides free-form mask, sketch and color as an input.

FACIAL INPAINTING

Omni-Scale Feature Learning for Person Re-Identification

ICCV 2019 KaiyangZhou/deep-person-reid

As an instance-level recognition problem, person re-identification (ReID) relies on discriminative features, which not only capture different spatial scales but also encapsulate an arbitrary combination of multiple scales.

PERSON RE-IDENTIFICATION

SinGAN: Learning a Generative Model from a Single Natural Image

ICCV 2019 tamarott/SinGAN

We introduce SinGAN, an unconditional generative model that can be learned from a single natural image.

IMAGE GENERATION

YOLACT: Real-time Instance Segmentation

ICCV 2019 dbolya/yolact

Then we produce instance masks by linearly combining the prototypes with the mask coefficients.

REAL-TIME INSTANCE SEGMENTATION SEMANTIC SEGMENTATION

FCOS: Fully Convolutional One-Stage Object Detection

ICCV 2019 tianzhi0549/FCOS

By eliminating the predefined set of anchor boxes, FCOS completely avoids the complicated computation related to anchor boxes such as calculating overlapping during training.

OBJECT DETECTION SEMANTIC SEGMENTATION