Sharing our vision at CVPR 2016

Published June 24, 2016

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By Andrew Fitzgibbon, Principal Researcher, Microsoft Research Cambridge

Photo by Jonathan Banks

This year, the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) will take place at Caesar’s Palace from June 26–July 1 in Las Vegas, Nevada. CVPR is the premier annual computer vision event that includes the main conference and several co-located workshops and short courses. With an international roster of speakers, exhibitors, and attendees, it provides an exceptional opportunity for students, academics, and industry researchers to meet and share ideas and research results.

I am thrilled to be serving as an Area Chair along with my colleague Jian Sun, from Microsoft Research Asia. Microsoft is a Platinum Sponsor this year, with over 25 papers being presented and 40 researchers, designers, and engineers attending from across the company, representing Xbox, HoloLens, Bing, and Microsoft Research.

One new and exciting addition to CVPR this year is for industrial and academic exhibitors. The Expo, which will be open during the entire CVPR event, is a unique opportunity for multiple worlds—academics, students, budding entrepreneurs, technologists, and others—to connect and catch up on the latest news and ideas. We hope you’ll spend time at the Expo, and check out our talks, tutorials, posters, and workshops (see schedule below). Also, please stop by our booth to chat with us about projects and opportunities at Microsoft, from pedal-to-the-metal engineering to research in pure mathematics.

Conference Details

Main Conference: June 27–June 30
Tutorials: June 26
Workshops: June 26, July 1
Industry Expo: June 27–June 30

Presentations (Main Conference)

(O)	Oral
(S)	Spotlight
(P)	Poster

Session		Title
Monday
(O) Mon a.m.		The Global Patch Collider
(O) Mon a.m.		Stacked Attention Networks for Image Question Answering
(P) Mon a.m.		Efficient and Robust Color Consistency for Community Photo Collections
(P) Mon a.m.		InterActive: Inter-Layer Activeness Propagation
(P) Mon a.m.		TI-POOLING: Transformation-Invariant Pooling for Feature Learning in Convolutional Neural Networks
(P) Mon p.m.		A Multi-Level Contextual Model for Person Recognition in Photo Albums
(S) Mon p.m.		Highlight Detection with Pairwise Deep Ranking for First-Person Video Summarization
(S) Mon p.m.		You Lead, We Exceed: Labor-Free Video Concept Learning by Jointly Exploiting Web Videos and Images
Tuesday
(P) Tue a.m.		Collaborative Quantization for Cross-Modal Similarity Search
(P) Tue a.m.		Supervised Quantization for Similarity Search
(P) Tue a.m.		Efficient Intersection of Three Quadrics and Applications in Computer Vision
(P) Tue a.m.		Image Deblurring Using Smartphone Inertial Sensors
(S) Tue a.m.		Large-Scale Location Recognition and the Geometric Burstiness Problem
(S) Tue p.m.		Do It Yourself Hyperspectral Imaging with Everyday Digital Cameras
Wednesday
(O) Wed a.m.		Instance-Aware Semantic Segmentation via Multi-Task Network Cascades
(P) Wed p.m.		Joint Recovery of Dense Correspondence and Cosegmentation in Two Images
(P) Wed a.m.		Sparse to Dense 3D Reconstruction from Rolling Shutter Images
(O) Wed a.m.		ScribbleSup: Scribble-Supervised Convolutional Networks for Semantic Segmentation
Thursday
(P) Thu a.m.		MSR-VTT: A Large Video Description Dataset for Bridging Video and Language
(P) Thu a.m.		Ordinal Regression with a Multiple Output CNN for Age Estimation
(P) Thu a.m.		DisturbLabel: Regularizing CNN on the Loss Layer
(O) Thu a.m.		Jointly Modeling Embedding and Translation to Bridge Video and Language
(O) Thu p.m.		HyperDepth: Learning Depth from Structured Light Without Matching
(S) Thu p.m.		Fits Like a Glove: Fast and Easy Hand Model Personalization
(S) Thu p.m.		Semantic 3D Reconstruction with Continuous Regularization and Ray Potentials Using a Visibility Consistency Constraint