Copyright and Reprint Permissions: Abstracting is permitted with credit to the source. Libraries may photocopy beyond the limits of US copyright law, for private use of patrons, those articles in this volume that carr...
Copyright and Reprint Permissions: Abstracting is permitted with credit to the source. Libraries may photocopy beyond the limits of US copyright law, for private use of patrons, those articles in this volume that carry a code at the bottom of the first page, provided that the per-copy fee indicated in the code is paid through the Copyright Clearance Center. The papers in this book comprise the proceedings of the meeting mentioned on the cover and title page. They reflect the authors' opinions and, in the interests of timely dissemination, are published as presented and without change. Their inclusion in this publication does not necessarily constitute endorsement by the editors or the Institute of Electrical and Electronics Engineers, Inc.
Copyright and Reprint Permissions: Abstracting is permitted with credit to the source. Libraries may photocopy beyond the limits of US copyright law, for private use of patrons, those articles in this volume that carr...
Copyright and Reprint Permissions: Abstracting is permitted with credit to the source. Libraries may photocopy beyond the limits of US copyright law, for private use of patrons, those articles in this volume that carry a code at the bottom of the first page, provided that the per-copy fee indicated in the code is paid through the Copyright Clearance Center. The papers in this book comprise the proceedings of the meeting mentioned on the cover and title page. They reflect the authors' opinions and, in the interests of timely dissemination, are published as presented and without change. Their inclusion in this publication does not necessarily constitute endorsement by the editors or the Institute of Electrical and Electronics Engineers, Inc.
The following topics are dealt with: image restoration of curved document images; image segmentation based stereo matching sequence using graph cuts; wavelet based hierarchial surface approximation using local feature...
The following topics are dealt with: image restoration of curved document images; image segmentation based stereo matching sequence using graph cuts; wavelet based hierarchial surface approximation using local feature subset selection; similarity measure and learning with Gray level aura matrices (GLAM) for texture image retrieval; 3D geometry models coding and morphing for efficient video compression; robust colour object detection using joint probability functions; generalized hidden Markov model; skew Gabor filter in source signal separation and local spectral analysis; motion estimation with optimization; Gibbs maximum likelihood estimation.
conference proceedings front matter may contain various advertisements, welcome messages, committee or program information, and other miscellaneous conference information. This may in some cases also include the cover...
ISBN:
(纸本)0769512720
conference proceedings front matter may contain various advertisements, welcome messages, committee or program information, and other miscellaneous conference information. This may in some cases also include the cover art, table of contents, copyright statements, title-page or half title-pages, blank pages, venue maps or other general information relating to the conference that was part of the original conference proceedings.
We demonstrate a concept of computervision as a secure, live service on the Internet. We show a platform to distribute a real lime vision algorithm using simple widely available web technologies, such as Adobe Flash....
详细信息
ISBN:
(纸本)9781424439942
We demonstrate a concept of computervision as a secure, live service on the Internet. We show a platform to distribute a real lime vision algorithm using simple widely available web technologies, such as Adobe Flash. We allow a user to access this service without downloading an executable or sharing the image stream with anyone. We support developers to publish without distribution complexity Finally the platform supports user-permitted aggregation of data for computervision research or analysis. We describe results a simple distributed motion detection algorithm. We discuss future scenarios for organically extending the horizon of computervision research.
This work presents AFRIFASHION1600, an openly accessible contemporary African fashion image dataset containing 1600 samples labelled into 8 classes representing some African fashion styles. Each sample is coloured and...
详细信息
ISBN:
(纸本)9781665448994
This work presents AFRIFASHION1600, an openly accessible contemporary African fashion image dataset containing 1600 samples labelled into 8 classes representing some African fashion styles. Each sample is coloured and has an image size of 128 x 128. This is a niche dataset that aims to improve visibility, inclusion, and familiarity of African fashion in computervision ***1600 dataset is available here.
Given a machine learning model, adversarial perturbations transform images such that the model's output is classified as an attacker chosen class. Most research in this area has focused on adversarial perturbation...
详细信息
ISBN:
(数字)9781538661000
ISBN:
(纸本)9781538661000
Given a machine learning model, adversarial perturbations transform images such that the model's output is classified as an attacker chosen class. Most research in this area has focused on adversarial perturbations that are imperceptible to the human eye. However, recent work has considered attacks that are perceptible but localized to a small region of the image. Under this threat model, we discuss both defenses that remove such adversarial perturbations, and attacks that can bypass these defenses.
Self-attention is a corner stone for transformer models. However, our analysis shows that self-attention in vision transformer inference is extremely sparse. When applying a sparsity constraint, our experiments on ima...
详细信息
ISBN:
(纸本)9781665448994
Self-attention is a corner stone for transformer models. However, our analysis shows that self-attention in vision transformer inference is extremely sparse. When applying a sparsity constraint, our experiments on image (ImageNet-1K) and video (Kinetics-400) understanding show we can achieve 95% sparsity on the self-attention maps while maintaining the performance drop to be less than 2 points. This motivates us to rethink the role of self-attention in vision transformer models.
The aim of this paper is to demonstrate that a state of the art feature matcher (LoFTR) can be made more robust to rotations by simply replacing the backbone CNN with a steerable CNN which is equivariant to translatio...
详细信息
ISBN:
(纸本)9781665487399
The aim of this paper is to demonstrate that a state of the art feature matcher (LoFTR) can be made more robust to rotations by simply replacing the backbone CNN with a steerable CNN which is equivariant to translations and image rotations. It is experimentally shown that this boost is obtained without reducing performance on ordinary illumination and viewpoint matching sequences.
In the context of variational auto-encoders, learning disentangled latent variable representations remains a challenging problem. In this abstract, we consider the semi-supervised setting, in which the factors of vari...
详细信息
ISBN:
(纸本)9781665448994
In the context of variational auto-encoders, learning disentangled latent variable representations remains a challenging problem. In this abstract, we consider the semi-supervised setting, in which the factors of variation are labelled for a small fraction of our samples. We examine how the quality of learned representations is affected by the dimension of the unsupervised component of the latent space. We also consider a variational lower bound for the mutual information between the data and the semi-supervised component of the latent space, and analyze its role in the context of disentangled representation learning.
暂无评论