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Mustafa Hajij; Mathilde Papillon; Florian Frantzen; Jens Agerberg; Ibrahem AlJabea; Ruben Ballester; Claudio Battiloro; Guillermo Bernardez; Tolga Birdal; Aiden Brent; Peter Chin; Sergio Escalera; Simone Fiorellino; Odin Hoff Gardaa; Gurusankar Gopalakrishnan; Devendra Govil; Josef Hoppe; Maneel Reddy Karri; Jude Khouja; Manuel Lecha; Neal Livesay; Jan Meibner; Soham Mukherjee; Alexander Nikitin; Theodore Papamarkou; Jaro Prilepok; Karthikeyan Natesan Ramamurthy; Paul Rosen; Aldo Guzman-Saenz; Alessandro Salatiello; Shreyas N. Samaga; Simone Scardapane; Michael T. Schaub; Luca Scofano; Indro Spinelli; Lev Telyatnikov; Quang Truong; Robin Walters; Maosheng Yang; Olga Zaghen; Ghada Zamzmi; Ali Zia; Nina Miolane |
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Title |
TopoX: A Suite of Python Packages for Machine Learning on Topological Domains |
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Miscellaneous |
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2024 |
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Arxiv |
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We introduce TopoX, a Python software suite that provides reliable and user-friendly building blocks for computing and machine learning on topological domains that extend graphs: hypergraphs, simplicial, cellular, path and combinatorial complexes. TopoX consists of three packages: TopoNetX facilitates constructing and computing on these domains, including working with nodes, edges and higher-order cells; TopoEmbedX provides methods to embed topological domains into vector spaces, akin to popular graph-based embedding algorithms such as node2vec; TopoModelx is built on top of PyTorch and offers a comprehensive toolbox of higher-order message passing functions for neural networks on topological domains. The extensively documented and unit-tested source code of TopoX is available under MIT license at this https URL. |
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Admin @ si @ HPF2024 |
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4021 |
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German Barquero; Sergio Escalera; Cristina Palmero |
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Title |
Seamless Human Motion Composition with Blended Positional Encodings |
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2024 |
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Arxiv |
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Conditional human motion generation is an important topic with many applications in virtual reality, gaming, and robotics. While prior works have focused on generating motion guided by text, music, or scenes, these typically result in isolated motions confined to short durations. Instead, we address the generation of long, continuous sequences guided by a series of varying textual descriptions. In this context, we introduce FlowMDM, the first diffusion-based model that generates seamless Human Motion Compositions (HMC) without any postprocessing or redundant denoising steps. For this, we introduce the Blended Positional Encodings, a technique that leverages both absolute and relative positional encodings in the denoising chain. More specifically, global motion coherence is recovered at the absolute stage, whereas smooth and realistic transitions are built at the relative stage. As a result, we achieve state-of-the-art results in terms of accuracy, realism, and smoothness on the Babel and HumanML3D datasets. FlowMDM excels when trained with only a single description per motion sequence thanks to its Pose-Centric Cross-ATtention, which makes it robust against varying text descriptions at inference time. Finally, to address the limitations of existing HMC metrics, we propose two new metrics: the Peak Jerk and the Area Under the Jerk, to detect abrupt transitions. |
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Admin @ si @ BEP2024 |
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4022 |
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Ayan Banerjee; Sanket Biswas; Josep Llados; Umapada Pal |
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GraphKD: Exploring Knowledge Distillation Towards Document Object Detection with Structured Graph Creation |
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2024 |
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Arxiv |
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Object detection in documents is a key step to automate the structural elements identification process in a digital or scanned document through understanding the hierarchical structure and relationships between different elements. Large and complex models, while achieving high accuracy, can be computationally expensive and memory-intensive, making them impractical for deployment on resource constrained devices. Knowledge distillation allows us to create small and more efficient models that retain much of the performance of their larger counterparts. Here we present a graph-based knowledge distillation framework to correctly identify and localize the document objects in a document image. Here, we design a structured graph with nodes containing proposal-level features and edges representing the relationship between the different proposal regions. Also, to reduce text bias an adaptive node sampling strategy is designed to prune the weight distribution and put more weightage on non-text nodes. We encode the complete graph as a knowledge representation and transfer it from the teacher to the student through the proposed distillation loss by effectively capturing both local and global information concurrently. Extensive experimentation on competitive benchmarks demonstrates that the proposed framework outperforms the current state-of-the-art approaches. The code will be available at: this https URL. |
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DAG |
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Admin @ si @ BBL2024b |
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4023 |
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Author |
C. Sbert; A.F. Sole |
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Stereo reconstruction of 3D curves. |
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Conference Article |
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2000 |
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15 th International Conference on Pattern Recognition |
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1 |
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912–915 |
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Barcelona. |
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Admin @ si @ SbS2000 |
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219 |
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J.M. Sanchez; X. Binefa |
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Color Normalization for Appearance Based Recognition of Video Key-frames. |
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Conference Article |
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2000 |
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15 th International Conference on Pattern Recognition |
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1 |
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815-818 |
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Barcelona. |
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Admin @ si @ SaB2000 |
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220 |
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Margarita Torre; Petia Radeva |
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Agricultural-Field Extraction on Aerial Images by Region Competition Algorithm |
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2000 |
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15 th International Conference on Pattern Recognition |
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1 |
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313-316 |
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Barcelona, Spain, 2000 |
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MILAB |
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BCNPCL @ bcnpcl @ Tor2000a |
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222 |
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Author |
J. Garcia; J.M. Sanchez; X. Orriols; X. Binefa |
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Chromatic aberration and depth extraction. |
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Conference Article |
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2000 |
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15 th International Conference on Pattern Recognition |
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1 |
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762-765 |
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Barcelona. |
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Admin @ si @ GSO2000 |
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226 |
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Author |
A. Pujol; Juan J. Villanueva; H. Wechsler |
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Automatic View Based Caricaturing. |
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2000 |
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15 th International Conference on Pattern Recognition |
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1 |
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1072-1075 |
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Barcelona. |
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ISE @ ise @ PVW2000 |
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227 |
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Author |
Francisco Jose Perales; Juan J. Villanueva; Yuhua Luo |
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Matching Criteria |
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1991 |
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Computer and Information Sciences VI, Proceedings of the 1991 International Symposium on Computer and Information Sciences |
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1 |
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1029-1038 |
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Antalya, Turkey, 30 October-2 November 1991 |
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Elsevier Science Pub. |
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0097-8493 |
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ISE @ ise @ PVL1991a |
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264 |
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Author |
Judit Martinez |
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Automotive sector and Machine Vision |
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2002 |
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European Integrated Machine Vision, Special Edition: Automative and Glass |
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1 |
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2 |
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Admin @ si @ 37316 |
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270 |
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Agata Lapedriza; David Masip; Jordi Vitria |
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On the Use of External Face Features for Identity Verification |
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2006 |
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Journal of Multimedia, 1(4): 11–20 |
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1 |
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4 |
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11-20 |
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Face Verification, Computer Vision, Machine Learning |
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In general automatic face classification applications images are captured in natural environments. In these cases, the performance is affected by variations in facial images related to illumination, pose, occlusion or expressions. Most of the existing face classification systems use only the internal features information, composed by eyes, nose and mouth, since they are more difficult to imitate. Nevertheless, nowadays a lot of applications not related to security are developed, and in these cases the information located at head, chin or ears zones (external features) can be useful to improve the current accuracies. However, the lack of a natural alignment in these areas makes difficult to extract these features applying classic Bottom-Up methods. In this paper, we propose a complete scheme based on a Top-Down reconstruction algorithm to extract external features of face images. To test our system we have performed face verification experiments using public databases, given that identity verification is a general task that has many real life applications. We have considered images uniformly illuminated, images with occlusions and images with high local changes in the illumination, and the obtained results show that the information contributed by the external features can be useful for verification purposes, specially significant when faces are partially occluded. |
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OR;MV |
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BCNPCL @ bcnpcl @ LMV2006b |
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708 |
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Author |
David Geronimo; Antonio Lopez; Angel Sappa |
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Title |
Computer Vision Approaches for Pedestrian Detection: Visible Spectrum Survey |
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2007 |
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3rd Iberian Conference on Pattern Recognition and Image Analysis, LNCS 4477 |
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1 |
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547–554 |
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Pedestrian detection |
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Pedestrian detection from images of the visible spectrum is a high relevant area of research given its potential impact in the design of pedestrian protection systems. There are many proposals in the literature but they lack a comparative viewpoint. According to this, in this paper we first propose a common framework where we fit the different approaches, and second we use this framework to provide a comparative point of view of the details of such different approaches, pointing out also the main challenges to be solved in the future. In summary, we expect
this survey to be useful for both novel and experienced researchers in the field. In the first case, as a clarifying snapshot of the state of the art; in the second, as a way to unveil trends and to take conclusions from the comparative study. |
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Girona (Spain) |
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J. Marti et al. |
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ADAS @ adas @ GLS2007 |
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804 |
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David Geronimo; Antonio Lopez; Daniel Ponsa; Angel Sappa |
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Haar Wavelets and Edge Orientation Histograms for On-Board Pedestrian Detection |
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2007 |
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3rd Iberian Conference on Pattern Recognition and Image Analysis, LNCS 4477 |
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1 |
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418–425 |
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Pedestrian detection |
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Girona (Spain) |
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J. Marti et al. |
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ADAS @ adas @ GLP2007a |
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805 |
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Author |
Joan Mas; Gemma Sanchez; Josep Llados; B. Lamiroy |
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An Incremental On-line Parsing Algorithm for Recognizing Sketching Diagrams |
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2007 |
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9th IEEE International Conference on Document Analysis and Recognition |
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1 |
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452–456 |
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Curitiba (Brazil) |
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ICDAR |
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DAG @ dag @ MSL2007a |
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847 |
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Josep Llados; Gemma Sanchez |
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Indexing Historical Documents by Word Shape Signatures |
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2007 |
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9th International Conference on Document Analysis and Recognition |
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1 |
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362–366 |
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Curitiba (Brasil) |
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Edition |
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DAG |
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DAG @ dag @ LlS2007 |
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882 |
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