489 citations · 1.9k across the 46 of their papers we have counts for
11 papers · 1 filter
Globally Consistent Multi-People Tracking using Motion Patterns
Andrii Maksai, Xinchao Wang, Francois Fleuret +1
Many state-of-the-art approaches to people tracking rely on detecting them in each frame independently, grouping detections into short but reliable trajectory segments, and then fu…
Active Learning and Proofreading for Delineation of Curvilinear Structures
Agata Mosinska, Jakub Tarnawski, Pascal Fua
Many state-of-the-art delineation methods rely on supervised machine learning algorithms. As a result, they require manually annotated training data, which is tedious to obtain. Fu…
Flight Dynamics-based Recovery of a UAV Trajectory using Ground Cameras
Artem Rozantsev, Sudipta N. Sinha, Debadeepta Dey +1
We propose a new method to estimate the 6-dof trajectory of a flying object such as a quadrotor UAV within a 3D airspace monitored using multiple fixed ground cameras. It is based…
Social Scene Understanding: End-to-End Multi-Person Action Localization and Collective Activity Recognition
Timur Bagautdinov, Alexandre Alahi, François Fleuret +2
We present a unified framework for understanding human social behaviors in raw image sequences. Our model jointly detects multiple individuals, infers their social actions, and est…
Multi-Modal Mean-Fields via Cardinality-Based Clamping
Pierre Baqué, François Fleuret, Pascal Fua
Mean Field inference is central to statistical physics. It has attracted much interest in the Computer Vision community to efficiently solve problems expressible in terms of large…
Monocular 3D Human Pose Estimation In The Wild Using Improved CNN Supervision
Dushyant Mehta, Helge Rhodin, Dan Casas +4
We propose a CNN-based approach for 3D human body pose estimation from single RGB images that addresses the issue of limited generalizability of models trained solely on the starkl…
Geometry in Active Learning for Binary and Multi-class Image Segmentation
Ksenia Konyushkova, Raphael Sznitman, Pascal Fua
We propose an active learning approach to image segmentation that exploits geometric priors to speed up and streamline the annotation process. It can be applied for both background…
Structured Prediction of 3D Human Pose with Deep Neural Networks
Bugra Tekin, Isinsu Katircioglu, Mathieu Salzmann +2
Most recent approaches to monocular 3D pose estimation rely on Deep Learning. They either train a Convolutional Neural Network to directly regress from image to 3D pose, which igno…
LIFT: Learned Invariant Feature Transform
Kwang Moo Yi, Eduard Trulls, Vincent Lepetit +1
We introduce a novel Deep Network architecture that implements the full feature point handling pipeline, that is, detection, orientation estimation, and feature description. While…
Beyond Sharing Weights for Deep Domain Adaptation
Artem Rozantsev, Mathieu Salzmann, Pascal Fua
The performance of a classifier trained on data coming from a specific domain typically degrades when applied to a related but different one. While annotating many samples from the…
Do We Need Binary Features for 3D Reconstruction?
Bin Fan, Qingqun Kong, Wei Sui +5
Binary features have been incrementally popular in the past few years due to their low memory footprints and the efficient computation of Hamming distance between binary descriptor…