CVPR 2019

Detect-to-Retrieve: Efficient Regional Aggregation for Image Search

CVPR 2019 tensorflow/models

Then, we demonstrate how a trained landmark detector, using our new dataset, can be leveraged to index image regions and improve retrieval accuracy while being much more efficient than existing regional methods.

IMAGE RETRIEVAL

FEELVOS: Fast End-to-End Embedding Learning for Video Object Segmentation

CVPR 2019 tensorflow/models

Many of the recent successful methods for video object segmentation (VOS) are overly complicated, heavily rely on fine-tuning on the first frame, and/or are slow, and are hence of limited practical use.

SEMANTIC SEGMENTATION VIDEO OBJECT SEGMENTATION VIDEO SEMANTIC SEGMENTATION

A Style-Based Generator Architecture for Generative Adversarial Networks

CVPR 2019 NVlabs/stylegan

We propose an alternative generator architecture for generative adversarial networks, borrowing from style transfer literature.

Temporal Cycle-Consistency Learning

CVPR 2019 google-research/google-research

We introduce a self-supervised representation learning method based on the task of temporal alignment between videos.

ANOMALY DETECTION REPRESENTATION LEARNING VIDEO ALIGNMENT

Pushing the Boundaries of View Extrapolation with Multiplane Images

CVPR 2019 google-research/google-research

We present a theoretical analysis showing how the range of views that can be rendered from an MPI increases linearly with the MPI disparity sampling frequency, as well as a novel MPI prediction procedure that theoretically enables view extrapolations of up to $4\times$ the lateral viewpoint movement allowed by prior work.

Unprocessing Images for Learned Raw Denoising

CVPR 2019 google-research/google-research

Machine learning techniques work best when the data used for training resembles the data used for evaluation.

IMAGE DENOISING

Panoptic Feature Pyramid Networks

CVPR 2019 facebookresearch/detectron2

In this work, we perform a detailed study of this minimally extended version of Mask R-CNN with FPN, which we refer to as Panoptic FPN, and show it is a robust and accurate baseline for both tasks.

INSTANCE SEGMENTATION PANOPTIC SEGMENTATION

Deformable ConvNets v2: More Deformable, Better Results

CVPR 2019 open-mmlab/mmdetection

The superior performance of Deformable Convolutional Networks arises from its ability to adapt to the geometric variations of objects.

INSTANCE SEGMENTATION OBJECT DETECTION SEMANTIC SEGMENTATION

Mask Scoring R-CNN

CVPR 2019 open-mmlab/mmdetection

In this paper, we study this problem and propose Mask Scoring R-CNN which contains a network block to learn the quality of the predicted instance masks.

INSTANCE SEGMENTATION SEMANTIC SEGMENTATION

Region Proposal by Guided Anchoring

CVPR 2019 open-mmlab/mmdetection

State-of-the-art detectors mostly rely on a dense anchoring scheme, where anchors are sampled uniformly over the spatial domain with a predefined set of scales and aspect ratios.

OBJECT DETECTION