USA-washington

下面是USA-washington的视觉人物信息

Liefeng Bo
http://research.cs.washington.edu/istc/lfb/
【Bio】Researcher at Amazon
【Focus on】image descriptors, boundary detection, image segmentation
【Code】

  • 2013 CVPR Multipath Sparse Coding Using Hierarchical Matching Pursuit
  • 2012 NIPS Discriminatively Trained Sparse Code Gradients for Contour Detection
  • 2012 CVPR RGB-(D) Scene Labeling: Features and Algorithms
  • 2011 NIPS Hierarchical Matching Pursuit for Image Classification: Architecture and Fast Algorithms
  • 2011 IROS Depth Kernel Descriptors for Object Recognition
  • 2010 NIPS Kernel Descriptors for Visual Recognition

Ira Kemelmacher-Shlizerman
http://homes.cs.washington.edu/~kemelmi/
【Bio】Assistant Professor
【Focus on】3-dimensional reconstruction, Visualization of massive photo collections, Synthesis and prediction of appearances, Planet-scale face recognition
【Code】

  • 2017 CVPR Level Playing Field for Million Scale Face Recognition
  • 2016 CVPR The MegaFace Benchmark: 1 Million Faces for Recognition at Scale

Ali Farhadi Ali Farhadi
http://homes.cs.washington.edu/~ali/index.html
【Bio】Assistant Professor
【Focus on】Object and action recognition, Multitask learning and annotation prediction, Image segmentation
【Code】

  • 2016 CVPR Situation Recognition: Visual Semantic Role Labeling for Image Understanding
  • 2016 CVPR Newtonian Image Understanding: Unfolding the Dynamics of Objects in Static Images
  • 2016 CVPR You Only Look Once: Unified, Real-Time Object Detection
  • 2016 ICML Unsupervised Deep Embedding for Clustering Analysis
  • 2012 ECCV Attribute Discovery via Predictable Discriminative Binary Codes

Xiaofeng Ren Xiaofeng Ren
http://homes.cs.washington.edu/~xren/
【Bio】researcher of Amazon,worked at Washington, PhD from UC Berkeley
【Focus on】image descriptors, boundary detection, image segmentation, figure-ground grouping, object and pose recognition, human body detection and pose estimation, object segmentation and tracking, and optical flow
【Code】

  • 2013 CVPR Histograms of Sparse Codes for Object Detection
  • 2013 CVPR Multipath Sparse Coding Using Hierarchical Matching Pursuit
  • 2013 IROS RGB-D Flow: Dense 3-D Motion Estimation Using Color and Depth
  • 2012 NIPS Discriminatively Trained Sparse Code Gradients for Contour Detection
  • 2012 ISER Unsupervised Feature Learning for RGB-D Based Object Recognition
  • 2012 CVPR RGB-(D) Scene Labeling: Features and Algorithms
  • 2011 NIPS Hierarchical Matching Pursuit for Image Classification: Architecture and Fast Algorithms
  • 2011 IROS Depth Kernel Descriptors for Object Recognition
  • 2010 NIPS Kernel Descriptors for Visual Recognition

Brian Curless Brian Curless
http://homes.cs.washington.edu/~curless/
【Bio】Professor
【Focus on】3D photography, Computational photography and videography, 3D interaction, Visualization
【Code】

  • 2011 CVPR Multicore Bundle Adjustment.
  • 2007 ESR Using Photographs to Enhance Videos of a Static Scene

Steven Seitz Steven Seitz
http://homes.cs.washington.edu/~seitz/
【Bio】Professor
【Focus on】Photo Collections, Image-Based Rendering and Illumination, 3D Shape Reconstruction, Motion and Animation, Vision for HCI


GRAIL GRAIL
http://grail.cs.washington.edu/
【Bio】Institute
【Focus on】Image-Based Rendering, 3D Shape Reconstruction
【Code】

  • Bundler: Structure from Motion for Unordered Image Collections.
  • Coordinate-free library from geometric processing: C version, C++ version.
  • CMVS: Clustering Views for Multi-view Stereo
  • GradientShop: A Gradient-Domain Optimization Framework for Image and Video Filtering
  • Multicore Bundle Adjustment software for 3D scene reconstruction.
  • Snoop: Onscreen magnification tool for Windows.
  • Surface reconstruction from unorganized points.
  • VisualSFM: A Visual “Structure from Motion” System.
  • VripPack: Volumetric range image processing package.

Pedro Domingos Pedro Domingos
http://homes.cs.washington.edu/~pedrod/
【Bio】Professor
【Focus on】Machine learning, Data mining
【Code】

  • Alchemy: Statistical relational AI.
  • SPN: Sum-product networks for tractable deep learning.
  • BVD: Bias-variance decomposition for zero-one loss.
  • NBE: Bayesian learner with very fast inference.
  • RISE: Unified rule- and instance-based learner.
  • VFML: Toolkit for mining massive data sources.

Neeraj Kumar Neeraj Kumar
http://homes.cs.washington.edu/~neeraj/
【Bio】Researcher of Dropbox, Postdoctor form Washington, PhD from Columbia
【Focus on】human faces, fine-grained visual categorization, large collections of real-world images for a variety of applications
【Code】

  • Leafsnap
  • Attribute Calibration Software
  • MugHunt Online Face Search Engine
  • Smileys Be Gone! source code
  • Compose-by-Chords Max/MSP code

【Dataset】

  • Leafsnap
  • Labeled Face Parts in the Wild (LFPW)
  • PubFig: Public Figures Face Database
  • FaceTracer Database

Santosh Divvala Santosh Divvala
http://homes.cs.washington.edu/~santosh/
【Bio】Researcher at AI2, Postdoc from Washington, PhD from CMU
【Focus on】Object recognition, Scene parsing
【Code】

  • A “lazy learning” framework (combination of kNN and SVM) for pedestrian detection the CALTECH dataset
  • Mexed version of Felzenszwalb segmentation code (to avoid the annoying reading/writing ppm images)
  • Fast implementation of the l1-distance. Uses SIMD compiler intrinsics and OpenMP parallelism for high speed

Li Zhang Li Zhang
http://pages.cs.wisc.edu/~lizhang/
【Bio】Researcher of google, Assistant professor of WISC, not updated since 2011
【Focus on】Semantic Image Analysis and Search,Computational Photography and Camera, 3D Reconstruction


Linda Shapiro Linda Shapiro
http://homes.cs.washington.edu/~shapiro/
【Bio】Professor
【Focus on】Object and Activity Recognition, Multimedia Information Retrieval,3D Object Recognition

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