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Author |
Javier Varona; Jordi Gonzalez; Xavier Roca; Juan J. Villanueva |
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Title |
Appearance Tracking for Video Surveillance |
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Miscellaneous |
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2003 |
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In Pattern Recognition and Image Analysis, Lecture Notes in Computer Science 2652:1041–1048 |
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ISE @ ise @ VGR2003b |
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425 |
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Author |
Jordi Gonzalez; Javier Varona; Xavier Roca; Juan J. Villanueva |
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Title |
Analysis of Human Walking Based on aSpaces |
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Miscellaneous |
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2004 |
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Articulated Motion and Deformable Objects, Third International Workshop, (AMDO 2004), Lecture Notes in Computer Science, F.J. Perales, B.A. Draper (Eds.), 3179:177–188 |
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Springer-Verlag, Berlin, Heidelberg |
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ISE @ ise @ GVR2004a |
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492 |
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Author |
Jordi Gonzalez; Javier Varona; Xavier Roca; Juan J. Villanueva |
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Title |
Situation Graph Trees for Human Behavior Modeling |
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2004 |
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7th Catalan Conference for Artificial Intelligence (CCIA’2004) |
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Barcelona (Spain) |
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ISE @ ise @ GVR2004b |
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498 |
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Author |
Ignasi Rius; Dani Rowe; Jordi Gonzalez; Xavier Roca |
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Title |
3D Action Modeling and Reconstruction for 2D Human Body Tracking |
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2005 |
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3rd International Conference on Advances in Pattern Recognition (ICAPR’2005), Pattern Recognition and Image Analysis, LNCS 3687: 146–154, ISBN 978–3–540–28833–6 |
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Bath (United Kingdom) |
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ISE @ ise @ RRG2005c |
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578 |
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Author |
V. Kober; Mikhail Mozerov; J. Alvarez-Borrego; I.A. Ovseyevich |
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Title |
Pattern Recognition of Fragmented Objects with Adaptive Correlation Filters |
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2006 |
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Topical Meeting on Optoinformatics / Information Photonics, 150–151 |
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Saint-Petersburg (Russia) |
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ISE |
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no |
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ISE @ ise @ KMA2006b |
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674 |
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Author |
Mikhail Mozerov; V. Kober; I.A. Ovseyevich |
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Title |
A Stereo Matching Algorithm with Global Smoothness Criterion |
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Miscellaneous |
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2006 |
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Topical Meeting on Optoinformatics / Information Photonics, 133–135 |
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Saint-Petersburg (Russia) |
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ISE |
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ISE @ ise @ MKO2006 |
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675 |
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Author |
Francisco Javier Orozco; Pau Baiget; Jordi Gonzalez; Xavier Roca |
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Title |
Eyelids and Face Tracking in Real-Time |
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2006 |
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6th IASTED International Conference Visualization, Imaging, and Image Processing (VIIP´06), 165–170 |
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Palma de Mallorca (Spain) |
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ISE |
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ISE @ ise @ OBG2006 |
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730 |
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Jose Manuel Alvarez; Felipe Lumbreras; Antonio Lopez; Theo Gevers |
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Understanding Road Scenes using Visual Cues |
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2012 |
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European Conference on Computer Vision |
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DEMO |
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Florence; Italy |
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ISE |
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Admin @ si @ ALL2012 |
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2795 |
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Author |
Marco Pedersoli |
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A Multiresolution Cascade for Human Detection |
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2008 |
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CVC Technical Report #126 |
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Barcelona, Spain |
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ISE |
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Admin @ si @ Ped2008 |
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1148 |
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Author |
Bhaskar Chakraborty |
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View-Invariant Human-Body Detection with Extension to Human Action Recognition using Component Wise HMM of Body Parts |
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Miscellaneous |
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2008 |
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CVC Technical Report #123 |
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Barcelona, Spain |
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ISE |
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Admin @ si @ Cha2008 |
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1149 |
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Anastasios Doulamis; Nikolaos Doulamis; Marco Bertini; Jordi Gonzalez; Thomas B. Moeslund |
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Analysis and Retrieval of Tracked Events and Motion in Imagery Streams |
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2013 |
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ACM/IEEE international workshop on Analysis and retrieval of tracked events and motion in imagery stream |
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Barcelona; October 2013 |
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ISE |
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Admin @ si @ DDB2013 |
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2372 |
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Author |
Bonifaz Stuhr; Jurgen Brauer; Bernhard Schick; Jordi Gonzalez |
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Title |
Masked Discriminators for Content-Consistent Unpaired Image-to-Image Translation |
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2023 |
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Arxiv |
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A common goal of unpaired image-to-image translation is to preserve content consistency between source images and translated images while mimicking the style of the target domain. Due to biases between the datasets of both domains, many methods suffer from inconsistencies caused by the translation process. Most approaches introduced to mitigate these inconsistencies do not constrain the discriminator, leading to an even more ill-posed training setup. Moreover, none of these approaches is designed for larger crop sizes. In this work, we show that masking the inputs of a global discriminator for both domains with a content-based mask is sufficient to reduce content inconsistencies significantly. However, this strategy leads to artifacts that can be traced back to the masking process. To reduce these artifacts, we introduce a local discriminator that operates on pairs of small crops selected with a similarity sampling strategy. Furthermore, we apply this sampling strategy to sample global input crops from the source and target dataset. In addition, we propose feature-attentive denormalization to selectively incorporate content-based statistics into the generator stream. In our experiments, we show that our method achieves state-of-the-art performance in photorealistic sim-to-real translation and weather translation and also performs well in day-to-night translation. Additionally, we propose the cKVD metric, which builds on the sKVD metric and enables the examination of translation quality at the class or category level. |
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Admin @ si @ SBS2023 |
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3863 |
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Author |
Wenjuan Gong; Y.Huang; Jordi Gonzalez; Liang Wang |
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Title |
An Effective Solution to Double Counting Problem in Human Pose Estimation |
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2015 |
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Arxiv |
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Pose estimation; double counting problem; mix-ture of parts Model |
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The mixture of parts model has been successfully applied to solve the 2D
human pose estimation problem either as an explicitly trained body part model
or as latent variables for pedestrian detection. Even in the era of massive
applications of deep learning techniques, the mixture of parts model is still
effective in solving certain problems, especially in the case with limited
numbers of training samples. In this paper, we consider using the mixture of
parts model for pose estimation, wherein a tree structure is utilized for
representing relations between connected body parts. This strategy facilitates
training and inferencing of the model but suffers from double counting
problems, where one detected body part is counted twice due to lack of
constrains among unconnected body parts. To solve this problem, we propose a
generalized solution in which various part attributes are captured by multiple
features so as to avoid the double counted problem. Qualitative and
quantitative experimental results on a public available dataset demonstrate the
effectiveness of our proposed method.
An Effective Solution to Double Counting Problem in Human Pose Estimation – ResearchGate. Available from: http://www.researchgate.net/publication/271218491AnEffectiveSolutiontoDoubleCountingProbleminHumanPose_Estimation [accessed Oct 22, 2015]. |
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ISE; 600.078 |
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Admin @ si @ GHG2015 |
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2590 |
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Guillem Cucurull; Pau Rodriguez; Vacit Oguz Yazici; Josep M. Gonfaus; Xavier Roca; Jordi Gonzalez |
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Title |
Deep Inference of Personality Traits by Integrating Image and Word Use in Social Networks |
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2018 |
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Arxiv |
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arXiv:1802.06757
Social media, as a major platform for communication and information exchange, is a rich repository of the opinions and sentiments of 2.3 billion users about a vast spectrum of topics. To sense the whys of certain social user’s demands and cultural-driven interests, however, the knowledge embedded in the 1.8 billion pictures which are uploaded daily in public profiles has just started to be exploited since this process has been typically been text-based. Following this trend on visual-based social analysis, we present a novel methodology based on Deep Learning to build a combined image-and-text based personality trait model, trained with images posted together with words found highly correlated to specific personality traits. So the key contribution here is to explore whether OCEAN personality trait modeling can be addressed based on images, here called MindPics, appearing with certain tags with psychological insights. We found that there is a correlation between those posted images and their accompanying texts, which can be successfully modeled using deep neural networks for personality estimation. The experimental results are consistent with previous cyber-psychology results based on texts or images.
In addition, classification results on some traits show that some patterns emerge in the set of images corresponding to a specific text, in essence to those representing an abstract concept. These results open new avenues of research for further refining the proposed personality model under the supervision of psychology experts. |
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ISE; 600.098; 600.119 |
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Admin @ si @ CRY2018 |
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3550 |
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Senmao Li; Joost van de Weijer; Taihang Hu; Fahad Shahbaz Khan; Qibin Hou; Yaxing Wang; Jian Yang |
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Title |
StyleDiffusion: Prompt-Embedding Inversion for Text-Based Editing |
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2023 |
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Arxiv |
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A significant research effort is focused on exploiting the amazing capacities of pretrained diffusion models for the editing of images. They either finetune the model, or invert the image in the latent space of the pretrained model. However, they suffer from two problems: (1) Unsatisfying results for selected regions, and unexpected changes in nonselected regions. (2) They require careful text prompt editing where the prompt should include all visual objects in the input image. To address this, we propose two improvements: (1) Only optimizing the input of the value linear network in the cross-attention layers, is sufficiently powerful to reconstruct a real image. (2) We propose attention regularization to preserve the object-like attention maps after editing, enabling us to obtain accurate style editing without invoking significant structural changes. We further improve the editing technique which is used for the unconditional branch of classifier-free guidance, as well as the conditional one as used by P2P. Extensive experimental prompt-editing results on a variety of images, demonstrate qualitatively and quantitatively that our method has superior editing capabilities than existing and concurrent works. |
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LAMP |
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Admin @ si @ LWH2023 |
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3870 |
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