ECCV 2016 - Amsterdam

14th European Conference on Computer Vision (ECCV), Amsterdam 2016

The European Conference on Computer Vision is one of the top conferences for researchers in this field and is held biennially in alternation with the International Conference on Computer Vision. It was first held in 1990 in Antibes (France) with subsequent conferences in Santa Margherita Ligure (Italy) in 1992, Stockholm (Sweden) in 1994, Cambridge (UK) in 1996, Freiburg (Germany) in 1998, Dublin (Ireland) in 2000, Copenhagen (Denmark) in 2002, Prague (Czech Republic) in 2004, Graz (Austria) in 2006, Marseille (France) in 2008, and Heraklion (Greece) in 2010 and 2012 in Florence (Italy). To our great delight, the 13th conference is held in Zürich, Switzerland.

ECCV has an established tradition of very high scientific quality and an overall duration of one week.

For more information please visit the ECCV 2016 website.

Categories

Top » Computer Science » Computer Vision


Opening
2111 views, 12:40 Opening remarksOpening remarks Nicu Sebe, Nicu Sebe, et al. Nicu Sebe, Nicu Sebe, Arnold Smeulders, Arnold Smeulders, Arnold Smeulders, Theo Gevers, Theo Gevers
Oral Session 1A: Detection, Recognition & Retrieval
[syn] 4437 views, 12:52 CNN Image Retrieval Learns from BoW: Unsupervised Fine-Tuning with Hard ExamplesCNN Image Retrieval Learns from BoW: Unsupervised Fine-Tuning with Hard ... Filip Radenović Filip Radenović	[syn] 5536 views, 14:11 SSD: Single Shot MultiBox DetectorSSD: Single Shot MultiBox Detector Dragomir Anguelov Dragomir Anguelov	1791 views, 10:58 A Recurrent Encoder-Decoder Network for Sequential Face AlignmentA Recurrent Encoder-Decoder Network for Sequential Face Alignment Xi Peng Xi Peng	[syn] 1725 views, 10:45 Robust Facial Landmark Detection via Recurrent Attentive-Refinement NetworksRobust Facial Landmark Detection via Recurrent Attentive-Refinement Networks Junliang Xing Junliang Xing
Spotlight Session 1A: Segmentation
[syn] 1555 views, 05:31 Learning to Refine Object SegmentsLearning to Refine Object Segments Pedro Pinheiro Pedro Pinheiro	[syn] 1929 views, 05:11 Deep Automatic Portrait MattingDeep Automatic Portrait Matting Xiaoyong Shen Xiaoyong Shen	[syn] 1368 views, 05:42 Segmentation from Natural Language ExpressionsSegmentation from Natural Language Expressions Ronghang Hu Ronghang Hu	[syn] 1853 views, 05:18 Semantic Object Parsing with Graph LSTMSemantic Object Parsing with Graph LSTM Xiaohui Shen Xiaohui Shen	[syn] 1326 views, 05:10 SSHMT: Semi-supervised Hierarchical Merge Tree for Electron Microscopy Image SegmentationSSHMT: Semi-supervised Hierarchical Merge Tree for Electron Microscopy Image Segmentation Ting Liu Ting Liu
Oral Session 1B: Scene Understanding
[syn] 1741 views, 13:39 Ambient Sound Provides Supervision for Visual LearningAmbient Sound Provides Supervision for Visual Learning Andrew Owens Andrew Owens	[syn] 1971 views, 13:06 Grounding of Textual Phrases in Images by ReconstructionGrounding of Textual Phrases in Images by Reconstruction Anna Rohrbach Anna Rohrbach	[syn] 1924 views, 10:25 Improving Multi-label Learning with Missing Labels by Structured Semantic CorrelationsImproving Multi-label Learning with Missing Labels by Structured Semantic Correlations Hao Yang Hao Yang	[syn] 4279 views, 12:05 Visual Relationship Detection with Language PriorsVisual Relationship Detection with Language Priors Ranjay Krishna Ranjay Krishna
Spotlight Session 1B: Recognition & Scene Understanding
[syn] 1386 views, 05:47 The Curious Robot: Learning Visual Representations via Physical InteractionsThe Curious Robot: Learning Visual Representations via Physical Interactions Lerrel Pinto Lerrel Pinto	1336 views, 04:54 Image Co-localization by Mimicking a Good Detector’s Confidence Score DistributionImage Co-localization by Mimicking a Good Detector’s Confidence Score Distribution Yao Li Yao Li	[syn] 1435 views, 05:11 Facilitating and Exploring Planar Homogeneous Texture for Indoor Scene UnderstandingFacilitating and Exploring Planar Homogeneous Texture for Indoor Scene Understanding Shahzor Ahmad Shahzor Ahmad	[syn] 1413 views, 05:41 An Empirical Study and Analysis of Generalized Zero-Shot Learning for Object Recognition in the WildAn Empirical Study and Analysis of Generalized Zero-Shot Learning for ... Wei-Lun Chao Wei-Lun Chao	[syn] 2290 views, 05:18 Modeling Context in Referring ExpressionsModeling Context in Referring Expressions Licheng Yu Licheng Yu
Oral Session 2A: Optimization
[syn] 1488 views, 11:06 An Efficient Fusion Move Algorithm for the Minimum Cost Lifted Multicut ProblemAn Efficient Fusion Move Algorithm for the Minimum Cost Lifted ... Thorsten Beier Thorsten Beier	[syn] 1582 views, 13:20 Sparse Subspace ClusteringSparse Subspace Clustering Yingzhen Yang Yingzhen Yang	[syn] 2594 views, 12:21 Normalized Cut meets MRFNormalized Cut meets MRF Meng Tang Meng Tang	[syn] 3999 views, 13:36 Fast Global RegistrationFast Global Registration Vladlen Koltun Vladlen Koltun 1 comment
Spotlight Session 2A: Optimization & Mathematical Models
[syn] 1321 views, 05:30 Similarity Search with Polysemous CodesSimilarity Search with Polysemous Codes Matthijs Douze Matthijs Douze	[syn] 1154 views, 05:16 Binary Hashing with Semidefinite Relaxation and Augmented LagrangianBinary Hashing with Semidefinite Relaxation and Augmented Lagrangian Thanh-Toan Do Thanh-Toan Do	[syn] 1355 views, 05:43 Efficient Continuous Relaxations for Dense CRFEfficient Continuous Relaxations for Dense CRF Alban Desmaison Alban Desmaison	[syn] 1235 views, 05:33 Complexity of Discrete Energy Minimization ProblemsComplexity of Discrete Energy Minimization Problems Alexander Shekhovtsov Alexander Shekhovtsov	[syn] 1171 views, 05:57 A Convex Solution to Spatially-Regularized Correspondence ProblemsA Convex Solution to Spatially-Regularized Correspondence Problems Thomas Windheuser Thomas Windheuser
Oral Session 2B: Image & Video Processing
[syn] 4149 views, 13:27 The Fast Bilateral SolverThe Fast Bilateral Solver Jonathan Barron Jonathan Barron	[syn] 10183 views, 16:32 Colorful Image ColorizationColorful Image Colorization Richard Zhang Richard Zhang	[syn] 2744 views, 13:42 Focal flow: Measuring depth and velocity from defocus and differential motionFocal flow: Measuring depth and velocity from defocus and differential ... Emma Alexander Emma Alexander
Spotlight Session 2B: Image Processing & Computational Photography
[syn] 1217 views, 05:35 An Evaluation of Computational Imaging Techniques for Heterogeneous Inverse ScatteringAn Evaluation of Computational Imaging Techniques for Heterogeneous Inverse Scattering Ioannis Gkioulekas Ioannis Gkioulekas	[syn] 1470 views, 05:35 Precomputed Real-Time Texture Synthesis with Markovian Generative Adversarial NetworksPrecomputed Real-Time Texture Synthesis with Markovian Generative Adversarial Networks Chuan Li Chuan Li	[syn] 1366 views, 05:41 Fast Guided Global Interpolation for Depth and MotionFast Guided Global Interpolation for Depth and Motion Jiangbo Lu Jiangbo Lu	[syn] 1202 views, 05:12 Learning High-Order Filters for Efficient Blind Deconvolution of Document PhotographsLearning High-Order Filters for Efficient Blind Deconvolution of Document Photographs Lei Xiao Lei Xiao	[syn] 1845 views, 05:44 Multi-View Inverse Rendering under Arbitrary Illumination and AlbedoMulti-View Inverse Rendering under Arbitrary Illumination and Albedo Akihiko Torii Akihiko Torii
Oral Session 3A: Learning
[syn] 8890 views, 13:00 XNOR-Net: ImageNet Classification Using Binary Convolutional Neural NetworksXNOR-Net: ImageNet Classification Using Binary Convolutional Neural Networks Mohammad Rastegari Mohammad Rastegari 8 comments	[syn] 1622 views, 15:11 Top-down Neural Attention by Excitation BackpropTop-down Neural Attention by Excitation Backprop Stan Sclaroff Stan Sclaroff	[syn] 3262 views, 13:35 Learning Recursive Filters for Low-Level Vision via a Hybrid Neural NetworkLearning Recursive Filters for Low-Level Vision via a Hybrid Neural ... Sifei Liu Sifei Liu 1 comment	[syn] 1490 views, 11:40 Learning Representations for Automatic ColorizationLearning Representations for Automatic Colorization Gustav Larsson Gustav Larsson
Spotlight Session 3A: CNNs
[syn] 1802 views, 05:08 Deep Reconstruction-Classification Networks for Unsupervised Domain AdaptationDeep Reconstruction-Classification Networks for Unsupervised Domain Adaptation Muhammad Ghifary Muhammad Ghifary	[syn] 3838 views, 05:43 Learning without ForgettingLearning without Forgetting Zhizhong Li Zhizhong Li	[syn] 1983 views, 05:24 Identity Mappings in Deep Residual NetworksIdentity Mappings in Deep Residual Networks Xiangyu Zhang Xiangyu Zhang	[syn] 2081 views, 05:47 Deep Networks with Stochastic DepthDeep Networks with Stochastic Depth Yu Sun Yu Sun	[syn] 2294 views, 05:31 Less is More: Towards Compact CNNsLess is More: Towards Compact CNNs Hao Zhou Hao Zhou
Spotlight Session 3B-3C: 3D & Structure from Motion
[syn] 1366 views, 05:32 When is Rotations Averaging Hard?When is Rotations Averaging Hard? Kyle Wilson Kyle Wilson	[syn] 1618 views, 05:11 Capturing Dynamic Textured Surfaces of Moving TargetsCapturing Dynamic Textured Surfaces of Moving Targets Hao Li Hao Li	[syn] 1190 views, 05:43 ShapeFit and ShapeKick for Robust, Scalable Structure from MotionShapeFit and ShapeKick for Robust, Scalable Structure from Motion Paul E. Hand Paul E. Hand	[syn] 1544 views, 05:38 Heat Diffusion Long-Short Term Memory Learning for 3D Shape AnalysisHeat Diffusion Long-Short Term Memory Learning for 3D Shape Analysis Fan Zhu Fan Zhu	[syn] 1482 views, 05:23 Multi-view 3D Models from Single Images With a Convolutional NetworkMulti-view 3D Models from Single Images With a Convolutional Network Maxim Tatarchenko Maxim Tatarchenko
[syn] 1676 views, 05:32 Linear depth estimation from an uncalibrated, monocular polarisation imageLinear depth estimation from an uncalibrated, monocular polarisation image William Smith William Smith	[syn] 1169 views, 05:26 Online Variational Bayesian Motion AveragingOnline Variational Bayesian Motion Averaging Guillaume Bourmaud Guillaume Bourmaud	[syn] 1613 views, 05:10 Unified Depth Prediction and Intrinsic Image Decomposition from a Single Image via Joint Convolutional Neural FieldsUnified Depth Prediction and Intrinsic Image Decomposition from a Single ... Seungryong Kim Seungryong Kim	[syn] 1519 views, 05:37 ObjectNet3D: A Large Scale Database for 3D Object RecognitionObjectNet3D: A Large Scale Database for 3D Object Recognition Christopher B. Choy Christopher B. Choy	[syn] 1186 views, 05:36 Branching Gaussian Processes with Applications to Spatiotemporal Reconstruction of 3D TreesBranching Gaussian Processes with Applications to Spatiotemporal Reconstruction of 3D ... Kyle Simek Kyle Simek
Oral Session 4A: 3D
[syn] 2135 views, 11:47 Real-Time 3D Reconstruction and 6-DoF Tracking with an Event CameraReal-Time 3D Reconstruction and 6-DoF Tracking with an Event Camera Hanme Kim Hanme Kim	[syn] 4533 views, 15:37 Single Image 3D Interpreter NetworkSingle Image 3D Interpreter Network Jiajun Wu Jiajun Wu	[syn] 1497 views, 14:57 Dual Structured Light 3D using a 1D SensorDual Structured Light 3D using a 1D Sensor Mohit Gupta Mohit Gupta	[syn] 1458 views, 15:07 Shape Acquisition and Registration for 3D Endoscope Based on Grid Pattern ProjectionShape Acquisition and Registration for 3D Endoscope Based on Grid ... Hiroshi Kawasaki Hiroshi Kawasaki
Spotlight Session 4A: Feature Extraction & Matching
[syn] 2633 views, 05:39 Target Response Adaptation for Correlation Filter TrackingTarget Response Adaptation for Correlation Filter Tracking Adel Bibi Adel Bibi	1568 views, 05:13 Learning Image Matching by Simply Watching VideoLearning Image Matching by Simply Watching Video Laurent Kneip Laurent Kneip 1 comment	[syn] 2202 views, 05:35 A Distance for HMMs based on Aggregated Wasserstein Metric and State RegistrationA Distance for HMMs based on Aggregated Wasserstein Metric and ... Yukun Chen Yukun Chen	[syn] 2365 views, 05:31 LIFT: Learned Invariant Feature TransformLIFT: Learned Invariant Feature Transform Kwang Moo Yi Kwang Moo Yi	[syn] 1758 views, 05:30 Learning a Predictable and Generative Vector Representation for ObjectsLearning a Predictable and Generative Vector Representation for Objects Rohit Girdhar Rohit Girdhar
Oral Session 4B: Action, Activity & Tracking
[syn] 1313 views, 10:02 Spot On: Action Localization from Pointly-Supervised ProposalsSpot On: Action Localization from Pointly-Supervised Proposals Pascal Mettes Pascal Mettes	1265 views, 13:31 Detecting Engagement in Egocentric VideoDetecting Engagement in Egocentric Video Yu-Chuan Su Yu-Chuan Su	[syn] 2262 views, 11:15 Beyond Correlation Filters: Learning Continuous Convolution Operators for Visual TrackingBeyond Correlation Filters: Learning Continuous Convolution Operators for Visual Tracking Martin Danelljan Martin Danelljan	[syn] 2047 views, 13:05 Look-Ahead Before You Leap: End-to-End Active Recognition by Forecasting the Effect of MotionLook-Ahead Before You Leap: End-to-End Active Recognition by Forecasting the ... Dinesh Jayaraman Dinesh Jayaraman 1 comment
Spotlight Session 4B: Human & Face
[syn] 1409 views, 05:37 General Automatic Human Shape and Motion Capture Using Volumetric Contour CuesGeneral Automatic Human Shape and Motion Capture Using Volumetric Contour ... Helge Rhodin Helge Rhodin	[syn] 1090 views, 05:38 Globally Continuous and Non-Markovian Activity Analysis from VideosGlobally Continuous and Non-Markovian Activity Analysis from Videos He Wang He Wang	[syn] 1947 views, 05:38 Joint Face Alignment and 3D Face ReconstructionJoint Face Alignment and 3D Face Reconstruction Feng Liu Feng Liu	[syn] 3077 views, 05:41 Keep it SMPL: Automatic Estimation of 3D Human Pose and Shape from a Single ImageKeep it SMPL: Automatic Estimation of 3D Human Pose and ... Angjoo Kanazawa Angjoo Kanazawa	[syn] 3063 views, 04:56 Do We Really Need to Collect Millions of Faces for Effective Face Recognition?Do We Really Need to Collect Millions of Faces for ... Iacopo Masi Iacopo Masi

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ECCV 2016 - Amsterdam

14th European Conference on Computer Vision (ECCV), Amsterdam 2016

Opening

Oral Session 1A: Detection, Recognition & Retrieval

Spotlight Session 1A: Segmentation

Oral Session 1B: Scene Understanding

Spotlight Session 1B: Recognition & Scene Understanding

Oral Session 2A: Optimization

Spotlight Session 2A: Optimization & Mathematical Models

Oral Session 2B: Image & Video Processing

Spotlight Session 2B: Image Processing & Computational Photography

Oral Session 3A: Learning

Spotlight Session 3A: CNNs

Spotlight Session 3B-3C: 3D & Structure from Motion

Oral Session 4A: 3D

Spotlight Session 4A: Feature Extraction & Matching

Oral Session 4B: Action, Activity & Tracking

Spotlight Session 4B: Human & Face

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