Zobrazeno 1 - 10
of 25
pro vyhledávání: '"Lubomir Bourdev"'
Publikováno v:
CVPR Workshops
Over the last few years deep learning methods have emerged as one of the most prominent approaches for video analysis. However, so far their most successful applications have been in the area of video classification and detection, i.e., problems invo
Publikováno v:
ICCV
With the widespread availability of cellphones and cameras that have GPS capabilities, it is common for images being uploaded to the Internet today to have GPS coordinates associated with them. In addition to research that tries to predict GPS coordi
Publikováno v:
ICCV
We propose a simple, yet effective approach for spatiotemporal feature learning using deep 3-dimensional convolutional networks (3D ConvNets) trained on a large scale supervised video dataset. Our findings are three-fold: 1) 3D ConvNets are more suit
Publikováno v:
KDD
Understanding the content of user's image posts is a particularly interesting problem in social networks and web settings. Current machine learning techniques focus mostly on curated training sets of image-label pairs, and perform image classificatio
Publikováno v:
CVPR
We explore the task of recognizing peoples' identities in photo albums in an unconstrained setting. To facilitate this, we introduce the new People In Photo Albums (PIPA) dataset, consisting of over 60000 instances of ∼2000 individuals collected fr
Publikováno v:
CVPR
This paper aims to classify and locate objects accurately and efficiently, without using bounding box annotations. It is challenging as objects in the wild could appear at arbitrary locations and in different scales. In this paper, we propose a novel
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c66af0996f5d23a97ec2ea12d4ec3894
Publikováno v:
CVPR
We propose a method for inferring human attributes (such as gender, hair style, clothes style, expression, action) from images of people under large variation of viewpoint, pose, appearance, articulation and occlusion. Convolutional Neural Nets (CNN)
Publikováno v:
BMVC
Poselets have been used in a variety of computer vision tasks, such as detection, segmentation, action classification, pose estimation and action recognition, often achieving state-of-the-art performance. Poselet evaluation, however, is computational
Publikováno v:
CVPR
We propose a novel approach for human pose estimation in real-world cluttered scenes, and focus on the challenging problem of predicting the pose of both arms for each person in the image. For this purpose, we build on the notion of poselets [4] and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::02938cfd97d1627958b744a66ea75899
https://resolver.caltech.edu/CaltechAUTHORS:20221215-789688000.2
https://resolver.caltech.edu/CaltechAUTHORS:20221215-789688000.2
Publikováno v:
CVPR
We address the problem of editing facial expression in video, such as exaggerating, attenuating or replacing the expression with a different one in some parts of the video. To achieve this we develop a tensor-based 3D face geometry reconstruction met