# SAUNet: Shape Attentive U-Net for Interpretable Medical Image Segmentation

21 Jan 2020sunjesse/shape-attentive-unet

Despite the progress of deep learning in medical image segmentation, standard CNNs are still not fully adopted in clinical settings as they lack robustness and interpretability.

0
21 Jan 2020

# Fast Sequence-Based Embedding with Diffusion Graphs

21 Jan 2020benedekrozemberczki/karateclub

A graph embedding is a representation of graph vertices in a low-dimensional space, which approximately preserves properties such as distances between nodes.

249
21 Jan 2020

# Evaluating Weakly Supervised Object Localization Methods Right

21 Jan 2020clovaai/wsolevaluation

In this paper, we argue that WSOL task is ill-posed with only image-level labels, and propose a new evaluation protocol where full supervision is limited to only a small held-out set not overlapping with the test set.

27
21 Jan 2020

# batchboost: regularization for stabilizing training with resistance to underfitting & overfitting

21 Jan 2020maciejczyzewski/batchboost

Pairing stage calculates the error per sample, sorts the samples and pairs with strategy: hardest with easiest one, than mixing stage merges two samples using mixup, $x_1 + (1-\lambda)x_2$.

1
21 Jan 2020

# Correcting Knowledge Base Assertions

19 Jan 2020ChenJiaoyan/KG_Curation

The usefulness and usability of knowledge bases (KBs) is often limited by quality issues.

1
19 Jan 2020

# Human-Aware Motion Deblurring

This paper proposes a human-aware deblurring model that disentangles the motion blur between foreground (FG) humans and background (BG).

34
19 Jan 2020

# See More, Know More: Unsupervised Video Object Segmentation with Co-Attention Siamese Networks

We introduce a novel network, called CO-attention Siamese Network (COSNet), to address the unsupervised video object segmentation task from a holistic view.

133
19 Jan 2020

# Learning Compositional Neural Information Fusion for Human Parsing

The bottom-up and top-down inferences explicitly model the compositional and decompositional relations in human bodies, respectively.

37
19 Jan 2020

# Zero-Shot Video Object Segmentation via Attentive Graph Neural Networks

Through parametric message passing, AGNN is able to efficiently capture and mine much richer and higher-order relations between video frames, thus enabling a more complete understanding of video content and more accurate foreground estimation.

76
19 Jan 2020

# Temporal Interlacing Network

17 Jan 2020deepcs233/TIN

In this way, a heavy temporal model is replaced by a simple interlacing operator.

9
17 Jan 2020