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Computer Vision

Enabling computers and devices to understand what they see.

Microsoft at CVPR 2024: Innovations in computer vision and AI research

DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models

Exploring how context, culture, and character matter in avatar research

FeatUp: A Model-Agnostic Framework for Features at Any Resolution

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Published Date

Publication

ScribbleSup: Scribble-Supervised Convolutional Networks for Semantic Segmentation

Di Lin, Jifeng Dai, Jiaya Jia, Kaiming He, Jian Sun

IEEE Conference on Computer Vision and Pattern Recognition (CVPR) | May 2016

Publication

A Super-Fast Online Face Tracking System for Video Surveillance

Xiaosong Lan, Zhiwei Xiong, Wei Zhang, Shuxiao li, Hongxing Chang, Wenjun Zeng

International Symposium on Circuits and Systems | May 2016

Publication

Deeply-Fused Nets

Jingdong Wang, Z. Wei, T. Zhang, Wenjun Zeng

May 2016

arXiv:1605.07716v1

Publication

Training Convolutional Neural Networks with Low-rank Filters for Efficient Image Classification

Yani Ioannou, Duncan Robertson, Jamie Shotton, Roberto Cipolla, Antonio Criminisi

Int Conf. on Learning Representations (ICLR) | April 2016

Publication

Generalisability of Image Quality Transfer: Can we approximate in-vivo human brains from dead monkey brains?

Aurobrata Ghosh, V. Wottschel, Enrico Kaden, H. Zhang, Stamatios N. Sotiropoulos, D. Zikic, T. B. Dyrby, Antonio Criminisi, Daniel C. Alexander

April 2016

Project Project

Publication

Beyond Geometric Path Planning: Learning Context-Driven Trajectory Preferences via Sub-optimal Feedback

Ashesh Jain, Shikhar Sharma, Ashutosh Saxena

Robotics Research: The 16th International Symposium ISRR | Published by Springer International Publishing | 2016

ISBN: 978-3-319-28872-7

Video

Learning to Propagate Information Across Pixels

April 11, 2016 | Varun Jampani

Natural images exhibit high information correlation across pixels. Bilateral filtering provide a simple yet powerful framework for information propagation across pixels. The common use-case is to manually choose a parametric filter type, usually a Gaussian…

1:11:49

Publication

Instance-sensitive Fully Convolutional Networks

Jifeng Dai, Kaiming He, Yi Li , Shaoqing Ren, Jian Sun

April 2016

Publication

Accuracy of Depth-Sensing Recordings in Classifying Expanded Disability Status Scale Subscores of Motor Dysfunction in Patients with Multiple Sclerosis (I8.004)

Marcus DSouza, Jessica Burggraaff, Saskia Steinheimer, Peter Kontschieder, Cecily Morrison, Jonas Dorn, Samuel Rota Bulò, Tewarie P, Kristina Miciunaite, Abigail Sellen, Dahlke F, Antonio Criminisi, Kamm C, Bernard Uitdehaag, Ludwig Kappos

Neurology | April 2016, Vol 86(16)

Publication

Accuracy of Depth-Sensing Recordings in Classifying Expanded Disability Status Scale Subscores of Motor Dysfunction in Patients with Multiple Sclerosis (I8.004)

Marcus D'Souza, Jessica Burggraaff, Saskia Steinheimer, Peter Kontschieder, Cecily Morrison, Jonas Dorn, Samuel Rota Bulò, Prejaas Tewarie, Kristina Miciunaite, Abigail Sellen, Antonio Criminisi, Frank Dahlke, Christian Kamm, Bernard Uitdehaag, Ludwig Kappos

Neurology | April 2016, Vol 86(16)

Project

Computer Vision

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