今日CS.CV計算機視覺論文速覽
Tue, 8 Jan 2019
Totally 43 papers

Interesting:

附加：第二部分補充

• Tencent ML-Images:騰訊釋出大規模多標籤資料集用於視覺表示學習。這一資料集包含了18M圖片和11K的分類標籤。用多標籤的資料有助於提高視覺表現學習的效果。(from Tencent AI Lab)
  資料集的統計資訊：
  
  code and 資料集： https://github.com/Tencent/tencent-ml-images
  分類標籤：http://data.mxnet.io/models/imagenet-11k/

  
  ref:ImageNet ,Caltech-256, object detection on PASCAL VOC 2007, semantic
  segmentation on PASCAL VOC 2012.
  tencent git：https://github.com/Tencent

• TridentNet，對於目標檢測任務提出了一種控制感受野大小來實現多尺度檢測的方法，使用共享引數來生成不同尺度的特徵圖，從而在不同的感受野大小上進行目標檢測。具體實現通過改變最後一層卷積的膨脹比例來實現不同大小的感受野的。同時，研究人員還提出了基於不同尺度的訓練方式，通過在不同尺度上提取合適的目標來訓練不同尺度的檢測分支,每個分支訓練檢測一定尺度範圍內的樣本

  。最終在COCO上達到了48.4的mAP。(from 中科院大學，圖森等)
  
  結果：
  
  知乎：https://zhuanlan.zhihu.com/p/54334986
  persons:https://www.zhihu.com/question/31168392/answer/50977180
  Detectron: https://github.com/facebookresearch/ Detectron/blob/master/MODEL_ZOO.md
  各種trick，包括sync BN，multi-scale training/testing，deformable conv，soft-nms

• 基於影象超分辨來防禦對抗樣本攻擊

  ,利用影象超分辨將對抗樣本從某一分類的流型外對映到對應標籤的流型內，從而使得人眼無法察覺的對抗樣本也能獲得正確的結果，阻止對抗攻擊。（from 智慧感知研究所 阿布扎比）
  超解析度恢復後頻譜分佈的有效性：
  
  特徵圖：
  
  code:https://github.com/aamir-mustafa/super-resolution-adversarial-defense
  ref:
  https://github.com/tensorflow/models/tree/master/research/slim
  https://github.com/tensorflow/cleverhans
  https://github.com/bethgelab/foolbox
  https://github.com/dongyp13/Non-Targeted-AdversarialAttacks
  https://github.com/cihangxie/DI-2-FGSM
  https://github.com/poloclub/jpeg-defense
  https://github.com/cihangxie/NIPS2017_adv_challenge_defense
  https://github.com/facebookresearch/adversarial_image_defenses
  https://github.com/iamaaditya/pixel-deflection
  Foolbox :生成對抗樣本的工具包

• 利用cycleGAN去除運動模糊，利用自編碼器架構來實現去模糊，並利用新穎的訓練策略恢復影象中的高頻訊號。(from 南京資訊工程大學)
  
  網路架構：
  
  連續的訓練策略，包括了從清晰圖生成模糊圖以及相反的過程：
  
  資料集樣本：
  
  資料集：GoPRO dataset:https://github.com/SeungjunNah/DeepDeblur_release
  ref:
  開源影象資料集總結：http://www.cnblogs.com/xiaojianliu/p/9446358.html
  語義影象修復資料集總結：https://github.com/moodoki/semantic_image_inpainting--》Dataset (CelebA) [23], the Street View HouseNumbers (SVHN) [29] and the Stanford Cars Dataset [17].
  GoPro-Gyro Dataset:http://www.cvl.isy.liu.se/research/datasets/gopro-gyro-dataset/

• 用於實時視覺追蹤更深更寬的孿生網路,雖然孿生網路在視覺最終中具有很大的優勢，但目前的基礎網路相對較淺。為了研究網路深度和寬度對效能的影響，研究人員先將基礎網路替換為ResNet和Inception等，但由於感受野變大使得特徵圖和定位精度下降，同時卷積補邊造成了學習位置的偏移。隨後研究人員提出了一種輕量級的實時殘差模組，用於消除補邊的影響，並利用新的架構控制感受野的大小。(from 中科院自動化所 微軟)
  文章中提出的內部裁剪殘差單元：
  
  dataset:OTB-15, VOT-16 and VOT-17 datasets
  related Method:SiamFC,SiamRPN SRDCF SINT Staple ECO-HC PTAV DSiam CFNet StructSiam TriSiam
  ref：https://www.cs.cmu.edu/~rsalakhu/papers/oneshot1.pdf
  https://blog.csdn.net/shenziheng1/article/details/81290893

• 基於空間相關性的人體位姿估計，文章中提出了分層連續預測融合(Cascade Prediction Fusion ,CPF) 和 位姿圖神經網路（Pose Graph Neural Network ，PGNN)來實現多級處理和潛在空間資訊的利用。（from 百度等）
  輔助預測到最終預測：
  
  網路架構圖：
  
  一些結果：
  
  資料集：MPII](http://human-pose.mpi-inf.mpg.de/)，LSP
  ref:https://github.com/asanakoy/deeppose_tf

• 少樣本情況下“想象”出三維模型，通過學習出某個類別一個通用的mesh，隨後旋轉視角匹配目標影象的視角得到小樣本下新目標的生成樣本，(from SAP)
  
  精煉的Self-paced結構：
  
  dataset： CUB-200-2011

• DSConv,Distribution Shifting Convolution一種新的卷積操作，將通常的卷積操作分為了變化量化核Variable Quantized Kernel (VQK)與分佈移動Distribution Shifts操作。通過VQK中的整數化操作減少記憶體提高速度，隨後通過分佈移動操作來保證輸出的質量。(from Oxford)
  
  訓練時DSC層的結構：
  
  訓練和推理的資料路徑：
  

• 通過無標籤的雙目資料學習出獨立個體的運動,可以通過雙目資料預測出目標的運動和例項掩膜，並得到每個物體的運動方向和速度。（from 伯克利）
  通過輸入流預測出深圖度和ROI區域的mask與流資訊。
  
  具體網路如下：
  
  一些結果：
  
  
  dataset:KITTI 2015，SYNTHIA dataset，Sintel dataset, FlyingChairsdataset, FlyingThings3D dataset
  相關方法：Epicflow，FlowNET,GeoNET,DF-Net，UnFlowC

• 基於幀間誤差預測精確的下一幀影象，（from 杭州科技大學）
  網路架構如下：
  
  生成器具體架構：
  
  資料集： UCF-101，KITTI.

• 預測虹膜以及分割
  ref:http://zbum.ia.pw.edu.pl/EN/node/2

Daily Computer Vision Papers

[1] Title: Learning Independent Object Motion from Unlabelled Stereoscopic Videos
Authors:Zhe Cao, Abhishek Kar, Christian Haene, Jitendra Malik
[2] Title: Graph- and finite element-based total variation models for the inverse problem in diffuse optical tomography
Authors:Wenqi Lu, Jinming Duan, David Orive-Miguel, Lionel Herve, Iain B Styles
[3] Title: GASL: Guided Attention for Sparsity Learning in Deep Neural Networks
Authors:Amirsina Torfi, Rouzbeh A. Shirvani, Sobhan Soleymani, Naser M. Nasrabadi
[4] Title: DSConv: Efficient Convolution Operator
Authors:Marcelo Gennari, Roger Fawcett, Victor Adrian Prisacariu
[5] Title: On the Global Geometry of Sphere-Constrained Sparse Blind Deconvolution
Authors:Yuqian Zhang, Yenson Lau, Han-Wen Kuo, Sky Cheung, Abhay Pasupathy, John Wright
[6] Title: Scale-Aware Trident Networks for Object Detection
Authors:Yanghao Li, Yuntao Chen, Naiyan Wang, Zhaoxiang Zhang
[7] Title: NVS Machines: Learning Novel View Synthesis with Fine-grained View Control
Authors:Xu Chen, Jie Song, Otmar Hilliges
[8] Title: Mutual Context Network for Jointly Estimating Egocentric Gaze and Actions
Authors:Yifei Huang, Minjie Cai, Zhenqiang Li, Yoichi Sato
[9] Title: Low-Shot Learning from Imaginary 3D Model
Authors:Frederik Pahde, Mihai Puscas, Jannik Wolff, Tassilo Klein, Nicu Sebe, Moin Nabi
[10] Title: Fusing Body Posture with Facial Expressions for Joint Recognition of Affect in Child-Robot Interaction
Authors:Panagiotis P. Filntisis, Niki Efthymiou, Petros Koutras, Gerasimos Potamianos, Petros Maragos
[11] Title: Human Pose Estimation with Spatial Contextual Information
Authors:Hong Zhang, Hao Ouyang, Shu Liu, Xiaojuan Qi, Xiaoyong Shen, Ruigang Yang, Jiaya Jia
[12] Title: Double Weighted Truncated Nuclear Norm Regularization for Low-Rank Matrix Completion
Authors:Shengke Xue, Wenyuan Qiu, Fan Liu, Xinyu Jin
[13] Title: Post-mortem Iris Recognition with Deep-Learning-based Image Segmentation
Authors:Mateusz Trokielewicz, Adam Czajka, Piotr Maciejewicz
[14] Title: Universal Deep Beamformer for Variable Rate Ultrasound Imaging
Authors:Shujaat Khan, Jaeyoung Huh, Jong Chul Ye
[15] Title: Tencent ML-Images: A Large-Scale Multi-Label Image Database for Visual Representation Learning
Authors:Baoyuan Wu, Weidong Chen, Yanbo Fan, Yong Zhang, Jinlong Hou, Junzhou Huang, Wei Liu, Tong Zhang
[16] Title: Image Super-Resolution as a Defense Against Adversarial Attacks
Authors:Aamir Mustafa, Salman H. Khan, Munawar Hayat, Jianbing Shen, Ling Shao
[17] Title: Deeper and Wider Siamese Networks for Real-Time Visual Tracking
Authors:Zhang Zhipeng, Peng Houwen, Wang Qiang
[18] Title: Tooth morphometry using quasi-conformal theory
Authors:Gary P. T. Choi, Hei Long Chan, Robin Yong, Sarbin Ranjitkar, Alan Brook, Grant Townsend, Ke Chen, Lok Ming Lui
[19] Title: Better Guider Predicts Future Better: Difference Guided Generative Adversarial Networks
Authors:Guohao Ying, Yingtian Zou, Lin Wan, Yiming Hu, Jiashi Feng
[20] Title: Blind Motion Deblurring with Cycle Generative Adversarial Networks
Authors:Quan Yuan, Junxia Li, Lingwei Zhang, Zhefu Wu, Guangyu Liu
[21] Title: Healthy versus pathological learning transferability in shoulder muscle MRI segmentation using deep convolutional encoder-decoders
Authors:Pierre-Henri Conze, Sylvain Brochard, Valérie Burdin, Frances T. Sheehan, Christelle Pons
[22] Title: CC-Net: Image Complexity Guided Network Compression for Biomedical Image Segmentation
Authors:Suraj Mishra, Peixian Liang, Adam Czajka, Danny Z. Chen, X. Sharon Hu
[23] Title: Learning-Free Iris Segmentation Revisited: A First Step Toward Fast Volumetric Operation Over Video Samples
Authors:Jeffery Kinnison, Mateusz Trokielewicz, Camila Carballo, Adam Czajka, Walter Scheirer
[24] Title: Transductive Zero-Shot Learning with Visual Structure Constraint
Authors:Ziyu Wan, Dongdong Chen, Yan Li, Xingguang Yan, Junge Zhang, Yizhou Yu, Jing Liao
[25] Title: Segmentation Guided Image-to-Image Translation with Adversarial Networks
Authors:Songyao Jiang, Zhiqiang Tao, Yun Fu
[26] Title: Automated Multiscale 3D Feature Learning for Vessels Segmentation in Thorax CT Images
Authors:Tomasz Konopczyński, Thorben Kröger, Lei Zheng, Christoph S. Garbe, Jürgen Hesser
[27] Title: Unsupervised uncertainty estimation using spatiotemporal cues in video saliency detection
Authors:Tariq Alshawi, Zhiling Long, Ghassan AlRegib
[28] Title: RayNet: Learning Volumetric 3D Reconstruction with Ray Potentials
Authors:Despoina Paschalidou, Ali Osman Ulusoy, Carolin Schmitt, Luc van Gool, Andreas Geiger
[29] Title: What Should I Do Now? Marrying Reinforcement Learning and Symbolic Planning
Authors:Daniel Gordon, Dieter Fox, Ali Farhadi
[30] Title: Bilinear Supervised Hashing Based on 2D Image Features
Authors:Yujuan Ding, Wai Kueng Wong, Zhihui Lai, Zheng Zhang
[31] Title: Early Prediction of Alzheimer’s Disease Dementia Based on Baseline Hippocampal MRI and 1-Year Follow-Up Cognitive Measures Using Deep Recurrent Neural Networks
Authors:Hongming Li, Yong Fan
[32] Title: Deep Convolutional Neural Networks for Imaging Data Based Survival Analysis of Rectal Cancer
Authors:Hongming Li, Pamela Boimel, James Janopaul-Naylor, Haoyu Zhong, Ying Xiao, Edgar Ben-Josef, Yong Fan
[33] Title: Forensic Shoe-print Identification: A Brief Survey
Authors:Imad Rida, Sambit Bakshi, Xiaojun Chang, Hugo Proenca
[34] Title: Curriculum Model Adaptation with Synthetic and Real Data for Semantic Foggy Scene Understanding
Authors:Dengxin Dai, Christos Sakaridis, Simon Hecker, Luc Van Gool
[35] Title: Brain segmentation based on multi-atlas guided 3D fully convolutional network ensembles
Authors:Jiong Wu, Xiaoying Tang
[36] Title: Stereoscopic Dark Flash for Low-light Photography
Authors:Jian Wang, Tianfan Xue, Jonathan Barron, Jiawen Chen
[37] Title: Adaptive Fusion for RGB-D Salient Object Detection
Authors:Ningning Wang, Xiaojin Gong
[38] Title: AVA-ActiveSpeaker: An Audio-Visual Dataset for Active Speaker Detection
Authors:Joseph Roth, Sourish Chaudhuri, Ondrej Klejch, Radhika Marvin, Andrew Gallagher, Liat Kaver, Sharadh Ramaswamy, Arkadiusz Stopczynski, Cordelia Schmid, Zhonghua Xi, Caroline Pantofaru
[39] Title: Generic Primitive Detection in Point Clouds Using Novel Minimal Quadric Fits
Authors:Tolga Birdal, Benjamin Busam, Nassir Navab, Slobodan Ilic, Peter Sturm
[40] Title: Understanding the (un)interpretability of natural image distributions using generative models
Authors:Ryen Krusinga, Sohil Shah, Matthias Zwicker, Tom Goldstein, David Jacobs
[41] Title: MAE: Mutual Posterior-Divergence Regularization for Variational AutoEncoders
Authors:Xuezhe Ma, Chunting Zhou, Eduard Hovy
[42] Title: Channel Locality Block: A Variant of Squeeze-and-Excitation
Authors:Huayu Li
[43] Title: Projective Decomposition and Matrix Equivalence up to Scale
Authors:Max Robinson

Papers from arxiv.org

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