output
19962026
most citedObservation of a new particle in the search for the Standard Model Higgs boson with the ATLAS detector at the LHC

10.9k citations

Showing 2018 · cs.CVShow all

13 papers · 2 filters

cs.CV2018★ 4 cited

MMFNet: A Multi-modality MRI Fusion Network for Segmentation of Nasopharyngeal Carcinoma

Huai Chen, Yuxiao Qi, Yong Yin +5

Segmentation of nasopharyngeal carcinoma (NPC) from Magnetic Resonance Images (MRI) is a crucial prerequisite for NPC radiotherapy. However, manually segmenting of NPC is time-cons…

cs.CV2018★ 16 cited

Super Diffusion for Salient Object Detection

Peng Jiang, Zhiyi Pan, Nuno Vasconcelos +2

One major branch of saliency object detection methods is diffusion-based which construct a graph model on a given image and diffuse seed saliency values to the whole graph by a dif…

cs.CV2018★ 18 cited

AUNet: Attention-guided dense-upsampling networks for breast mass segmentation in whole mammograms

Hui Sun, Cheng Li, Boqiang Liu +3

Mammography is one of the most commonly applied tools for early breast cancer screening. Automatic segmentation of breast masses in mammograms is essential but challenging due to t…

cs.CV2018★ 55 cited

Deeply Supervised Depth Map Super-Resolution as Novel View Synthesis

Xibin Song, Yuchao Dai, Xueying Qin

Deep convolutional neural network (DCNN) has been successfully applied to depth map super-resolution and outperforms existing methods by a wide margin. However, there still exist t…

cs.CV2018★ 7 cited

Decouple Learning for Parameterized Image Operators

Qingnan Fan, Dongdong Chen, Lu Yuan +3

Many different deep networks have been used to approximate, accelerate or improve traditional image operators, such as image smoothing, super-resolution and denoising. Among these…

cs.CV2018★ 6 cited

SketchyScene: Richly-Annotated Scene Sketches

Changqing Zou, Qian Yu, Ruofei Du +6

We contribute the first large-scale dataset of scene sketches, SketchyScene, with the goal of advancing research on sketch understanding at both the object and scene level. The dat…