手还在的,来读读这43篇AI论文

重磅干货,第一时间送达

前戏:双十一

本来,Amusi 双十一不打算shopping。但想了想,购物嘛,就是图个开心。没有必要因为自己不买而省钱,沾沾自喜;也没有必要因为自己买买买,而精神舒坦。

学生时代的我们,就是没啥钱。我主张的是能力范围内,去shopping就行了。那些平时不舍得买的东西,其实可以年末奖励一下自己。人嘛,就是图个开心,享受还是要享受的,因为人生苦短嘛。奢侈一回儿,顶多一个月泡面走起嘛...

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计算机视觉论文速递

一些读者反映,有质量的文章越来越少了,我在此申明一下:整理简单原创的计算机视觉论文速度文章,其实也比较花时间(当然了,论文精读也比较花时间,特别是整理好细节形成推文的规格)。

其实每天的paper,我都在整理,但我只会在私人的知识星球里发送,也因为那是给自己看的,比较简单粗暴,所以不足以达到可以自认为微信推文的高度。

CVer 私人星球,我搁了很久,目前不打算宣传,因为就是怕有人说割韭菜,真的一言难尽。

本文就将这一周的计算机视觉论文速递po出来,没有摘要哈,大家看标题感兴趣的,就根据相应的链接去沉浸在学术的汪洋里吧。

Paper Date:2018-11-05 ~11-09

数据集

《The Open Images Dataset V4: Unified image classification, object detection, and visual relationship detection at scale》

IJCV

arXiv:https://arxiv.org/abs/1811.00982

数据集官网:https://storage.googleapis.com/openimages/web/index.html

注:920w 幅图像

《Toward Driving Scene Understanding: A Dataset for Learning Driver Behavior and Causal Reasoning》

CVPR 2018

arXiv:https://arxiv.org/abs/1811.02307

datasets:https://usa.honda-ri.com/hdd

CNN

《Invertible Residual Networks》

arXiv:https://arxiv.org/abs/1811.00995

《You Only Search Once: Single Shot Neural Architecture Search via Direct Sparse Optimization》

ICLR2019 Submission

arXiv:https://arxiv.org/abs/1811.01567

注:图森中实习生的work,超越NAS

《Bi-Real Net: Binarizing Deep Network Towards Real-Network Performance》

Submitted to IJCV 2018

arXiv:https://arxiv.org/abs/1811.01335

《Activation Functions: Comparison of trends in Practice and Research for Deep Learning》

arXiv:https://arxiv.org/abs/1811.03378

《Microscopic Nuclei Classification, Segmentation and Detection with improved Deep Convolutional Neural Network (DCNN) Approaches》

arXiv:https://arxiv.org/abs/1811.03447

《ColorUNet: A convolutional classification approach to colorization》

arXiv:https://arxiv.org/abs/1811.03120

《ExGate: Externally Controlled Gating for Feature-based Attention in Artificial Neural Networks》

arXiv:https://arxiv.org/abs/1811.03403

图像分类

《Learning from Large-scale Noisy Web Data with Ubiquitous Reweighting for Image Classification》

arXiv:https://arxiv.org/abs/1811.00700

数据增广

《Hide-and-Seek: A Data Augmentation Technique for Weakly-Supervised Localization and Beyond》

TPAMI

arXiv:https://arxiv.org/abs/1811.02545

Face

《Exposing DeepFake Videos By Detecting Face Warping Artifacts》

arXiv:https://arxiv.org/abs/1811.00656

《Exposing Deep Fakes Using Inconsistent Head Poses》

arXiv:https://arxiv.org/abs/1811.00661

《Fast Face Image Synthesis with Minimal Training》

WACV 2019

arXiv:https://arxiv.org/abs/1811.01474

datasets:https://cvrl.nd.edu/projects/data/

《Facial Landmark Detection for Manga Images》

arXiv:https://arxiv.org/abs/1811.03214

特定目标检测

《Real-time Driver Drowsiness Detection for Android Application Using Deep Neural Networks Techniques》

arXiv:https://arxiv.org/abs/1811.01627

《Query-based Logo Segmentation》

arXiv:https://arxiv.org/abs/1811.01395

图像分割

《Prediction Error Meta Classification in Semantic Segmentation: Detection via Aggregated Dispersion Measures of Softmax Probabilities》

arXiv:https://arxiv.org/abs/1811.00648

《Unsupervised RGBD Video Object Segmentation Using GANs》

ACCV workshop

arXiv:https://arxiv.org/abs/1811.01526

《DUNet: A deformable network for retinal vessel segmentation》

arXiv:https://arxiv.org/abs/1811.01206

《Ischemic Stroke Lesion Segmentation in CT Perfusion Scans using Pyramid Pooling and Focal Loss》

2018 MICCAI workshop

arXiv:https://arxiv.org/abs/1811.01085

《An End-to-end Approach to Semantic Segmentation with 3D CNN and Posterior-CRF in Medical Images》

NIPS 2018 Workshop

arXiv:https://arxiv.org/abs/1811.03549

《Adaptive Semantic Segmentation with a Strategic Curriculum of Proxy Labels》

arXiv:https://arxiv.org/abs/1811.03542

《Deep Semantic Instance Segmentation of Tree-like Structures Using Synthetic Data》

WACV 2019

arXiv:https://arxiv.org/abs/1811.03208

GAN

《Improving GAN with neighbors embedding and gradient matching》

AAAI 2019

arXiv:https://arxiv.org/abs/1811.01333

《A General Theory of Equivariant CNNs on Homogeneous Spaces》

arXiv:https://arxiv.org/abs/1811.02017

《Triple consistency loss for pairing distributions in GAN-based face synthesis》

arXiv:https://arxiv.org/abs/1811.03492

github:https://github.com/ESanchezLozano/GANnotation

youtube:https://youtu.be/-8r7zexg4yg

OCR

《Auto-ML Deep Learning for Rashi Scripts OCR》

arXiv:https://arxiv.org/abs/1811.01290

不规则文字识别

《Show, Attend and Read: A Simple and Strong Baseline for Irregular Text Recognition》

arXiv:https://arxiv.org/abs/1811.00751

风格迁移

《Evolvement Constrained Adversarial Learning for Video Style Transfer》

arXiv:https://arxiv.org/abs/1811.02476

竞赛Workshop

《Introduction to the 1st Place Winning Model of OpenImages Relationship Detection Challenge》

arXiv:https://arxiv.org/abs/1811.00662

姿态估计

《Improving Multi-Person Pose Estimation using Label Correction》

arXiv:https://arxiv.org/abs/1811.03331

目标跟踪

《High Speed Tracking With A Fourier Domain Kernelized Correlation Filter》

arXiv:https://arxiv.org/abs/1811.03236

Zero-shot Learning

《Model Selection for Generalized Zero-shot Learning》

arXiv:https://arxiv.org/abs/1811.03252

3D

《SPNet: Deep 3D Object Classification and Retrieval using Stereographic Projection》

arXiv:https://arxiv.org/abs/1811.01571

滤波

《Fast Adaptive Bilateral Filtering》

TIP

arXiv:https://arxiv.org/abs/1811.02308

《Fast High-Dimensional Bilateral and Nonlocal Means Filtering》

TIP

arXiv:https://arxiv.org/abs/1811.02363

其它

《Continual Occlusions and Optical Flow Estimation》

ACCV 2018

arXiv:https://arxiv.org/abs/1811.01602

《Texture Synthesis Guided Deep Hashing for Texture Image Retrieval》

arXiv:https://arxiv.org/abs/1811.01401

《Semantic bottleneck for computer vision tasks》

ACCV 2018

arXiv:https://arxiv.org/abs/1811.02234

《3DCapsule: Extending the Capsule Architecture to Classify 3D Point Clouds》

WACV 2019

arXiv:https://arxiv.org/abs/1811.02191

《Automatic Thresholding of SIFT Descriptors》

ICIP 2016

arXiv:https://arxiv.org/abs/1811.03173

《DragonPaint: Rule based bootstrapping for small data with an application to cartoon coloring》

arXiv:https://arxiv.org/abs/1811.03151

授之以鱼,不如授之以渔。希望上面的论文,可以给各位CVer提供一点点灵感

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