Papers
BPGrad: Towards Global Optimality in Deep Learning via Branch and Pruning
Ziming Zhang, Yuanwei Wu, Guanghui Wang
Learning to See in the Dark
Chen Chen, Qifeng Chen, Jia Xu et al.
Boundary Flow: A Siamese Network That Predicts Boundary Motion Without Training on Motion
Peng Lei, Fuxin Li, Sinisa Todorovic
Non-Blind Deblurring: Handling Kernel Uncertainty With CNNs
Subeesh Vasu, Venkatesh Reddy Maligireddy, A. N. Rajagopalan
Learning a Single Convolutional Super-Resolution Network for Multiple Degradations
Kai Zhang, Wangmeng Zuo, Lei Zhang
Gated Fusion Network for Single Image Dehazing
Wenqi Ren, Lin Ma, Jiawei Zhang et al.
Flow Guided Recurrent Neural Encoder for Video Salient Object Detection
Guanbin Li, Yuan Xie, Tianhao Wei et al.
Erase or Fill? Deep Joint Recurrent Rain Removal and Reconstruction in Videos
Jiaying Liu, Wenhan Yang, Shuai Yang et al.
Deep Video Super-Resolution Network Using Dynamic Upsampling Filters Without Explicit Motion Compensation
Younghyun Jo, Seoung Wug Oh, Jaeyeon Kang et al.
Learning Convolutional Networks for Content-Weighted Image Compression
Mu Li, Wangmeng Zuo, Shuhang Gu et al.
Universal Denoising Networks : A Novel CNN Architecture for Image Denoising
Stamatios Lefkimmiatis
Densely Connected Pyramid Dehazing Network
He Zhang, Vishal M. Patel
Active Fixation Control to Predict Saccade Sequences
Calden Wloka, Iuliia Kotseruba, John K. Tsotsos
MoNet: Moments Embedding Network
Mengran Gou, Fei Xiong, Octavia Camps et al.
Multi-Scale Weighted Nuclear Norm Image Restoration
Noam Yair, Tomer Michaeli
Image Blind Denoising With Generative Adversarial Network Based Noise Modeling
Jingwen Chen, Jiawei Chen, Hongyang Chao et al.
KIPPI: KInetic Polygonal Partitioning of Images
Jean-Philippe Bauchet, Florent Lafarge
Beyond the Pixel-Wise Loss for Topology-Aware Delineation
Agata Mosinska, Pablo Márquez-Neila, Mateusz Koziński et al.
Detect Globally, Refine Locally: A Novel Approach to Saliency Detection
Tiantian Wang, Lihe Zhang, Shuo Wang et al.
“Zero-Shot” Super-Resolution Using Deep Internal Learning
Assaf Shocher, Nadav Cohen, Michal Irani
What Do Deep Networks Like to See?
Sebastian Palacio, Joachim Folz, Jörn Hees et al.
Curve Reconstruction via the Global Statistics of Natural Curves
Ehud Barnea, Ohad Ben-Shahar
PiCANet: Learning Pixel-Wise Contextual Attention for Saliency Detection
Nian Liu, Junwei Han, Ming-Hsuan Yang
Defocus Blur Detection via Multi-Stream Bottom-Top-Bottom Fully Convolutional Network
Wenda Zhao, Fan Zhao, Dong Wang et al.
Learning Dual Convolutional Neural Networks for Low-Level Vision
Jinshan Pan, Sifei Liu, Deqing Sun et al.