Outputs (187)

Fg-T2M: Fine-Grained Text-Driven Human Motion Generation via Diffusion Model (2023)
Presentation / Conference Contribution
Wang, Y., Leng, Z., Li, F. W. B., Wu, S., & Liang, X. (2023). Fg-T2M: Fine-Grained Text-Driven Human Motion Generation via Diffusion Model. In 2023 IEEE/CVF International Conference on Computer Vision (ICCV). https://doi.org/10.1109/ICCV51070.2023.02014

Text-driven human motion generation in computer vision is both significant and challenging. However, current methods are limited to producing either deterministic or imprecise motion sequences, failing to effectively control the temporal and spatial... Read More about Fg-T2M: Fine-Grained Text-Driven Human Motion Generation via Diffusion Model.

On Isotropy, Contextualization and Learning Dynamics of Contrastive-based Sentence Representation Learning (2023)
Presentation / Conference Contribution
Xiao, C., Long, Y., & Al Moubayed, N. (2023). On Isotropy, Contextualization and Learning Dynamics of Contrastive-based Sentence Representation Learning. . https://doi.org/10.18653/v1/2023.findings-acl.778

Anomaly Detection with Transformers in Face Anti-spoofing (2023)
Presentation / Conference Contribution
Abduh, L., Omar, L., & Ivrissimtzis, I. (2023). Anomaly Detection with Transformers in Face Anti-spoofing. . https://doi.org/10.24132/JWSCG.2023.10

Transformers are emerging as the new gold standard in various computer vision applications, and have already been used in face anti-spoofing demonstrating competitive performance. In this paper, we propose a network with the ViT transformer and ResNe... Read More about Anomaly Detection with Transformers in Face Anti-spoofing.

DrawGAN: Multi-view Generative Model Inspired By The Artist's Drawing Method (2023)
Presentation / Conference Contribution
Yang, B., Chen, Z., Li, F. W. B., Sun, H., & Cai, J. (2023). DrawGAN: Multi-view Generative Model Inspired By The Artist's Drawing Method. In B. Sheng, L. Bi, J. Kim, N. Magnenat-Thalmann, & D. Thalmann (Eds.), Advances in Computer Graphics 40th Computer Graphics International Conference, CGI 2023, Shanghai, China, August 28–September 1, 2023, Proceedings, Part II (479-490). https://doi.org/10.1007/978-3-031-50072-5_38

We present a novel approach for modeling artists' drawing processes using an architecture that combines an unconditional generative adversarial network (GAN) with a multi-view generator and multi-discriminator. Our method excels in synthesizing vario... Read More about DrawGAN: Multi-view Generative Model Inspired By The Artist's Drawing Method.

Innovative haptic-based system for upper limb rehabilitation in visually impaired individuals: a multilayer approach (2023)
Journal Article
Albusac, J., Herrera, V., Schez-Sobrino, S., Grande, R., Vallejo, D., & Monekosso, D. (2024). Innovative haptic-based system for upper limb rehabilitation in visually impaired individuals: a multilayer approach. Multimedia Tools and Applications, 83(21), 60537-60563. https://doi.org/10.1007/s11042-023-17892-4

The integration of technology in healthcare has revolutionized physical rehabilitation of patients affected by neurological conditions, such as spinal cord injuries and strokes. However, a significant gap remains in addressing the needs of the visual... Read More about Innovative haptic-based system for upper limb rehabilitation in visually impaired individuals: a multilayer approach.

Trustworthy IAP: An Intelligent Applications Profiler to Investigate Vulnerabilities of Consumer Electronic Devices (2023)
Journal Article
Su, J., Hong, Z., Ye, L., Liu, T., Liang, S., Ji, S., …Wen, Z. (2023). Trustworthy IAP: An Intelligent Applications Profiler to Investigate Vulnerabilities of Consumer Electronic Devices. IEEE Transactions on Consumer Electronics, https://doi.org/10.1109/tce.2023.3347651

As a typical representative of the Internet of Energy (IoE) intelligent era, consumer electronic (CE) devices continue to evolve at a remarkable pace. Computers, as typical and essential CE devices, have been instrumental in enhancing efficiency, com... Read More about Trustworthy IAP: An Intelligent Applications Profiler to Investigate Vulnerabilities of Consumer Electronic Devices.

Modeling Women's Elective Choices in Computing (2023)
Presentation / Conference Contribution
Bradley, S., Parker, M. C., Altin, R., Barker, L., Hooshangi, S., Kunkeler, T., …Sibia, N. (2023). Modeling Women's Elective Choices in Computing. . https://doi.org/10.1145/3623762.3633497

Evidence-based strategies suggest ways to reduce the gender gap in computing. For example, elective classes are valuable in enabling students to choose in which directions to expand their computing knowledge in areas aligned with their interests. T... Read More about Modeling Women's Elective Choices in Computing.

Automated Provenance Collection at Runtime as a Cross-Cutting Concern (2023)
Presentation / Conference Contribution
James Reynolds, O., García-Domínguez, A., & Bencomo, N. (2023). Automated Provenance Collection at Runtime as a Cross-Cutting Concern. In 2023 ACM/IEEE International Conference on Model Driven Engineering Languages and Systems Companion (MODELS-C) (276-285). https://doi.org/10.1109/MODELS-C59198.2023.00057

Autonomous decision-making is increasingly applied to handle highly dynamic, uncertain environments: as incorrect decisions can cause serious harm to individuals or society, there is a need for accountability. For systems that use runtime models to r... Read More about Automated Provenance Collection at Runtime as a Cross-Cutting Concern.

FedBoosting: Federated learning with gradient protected boosting for text recognition (2023)
Journal Article
Ren, H., Deng, J., Xie, X., Ma, X., & Wang, Y. (2024). FedBoosting: Federated learning with gradient protected boosting for text recognition. Neurocomputing, 569, Article 127126. https://doi.org/10.1016/j.neucom.2023.127126

Conventional machine learning methodologies require the centralization of data for model training, which may be infeasible in situations where data sharing limitations are imposed due to concerns such as privacy and gradient protect... Read More about FedBoosting: Federated learning with gradient protected boosting for text recognition.

List 3-Coloring on Comb-Convex and Caterpillar-Convex Bipartite Graphs (2023)
Presentation / Conference Contribution
Baklan Sen, B., Diner, Ö. Y., & Erlebach, T. (2023). List 3-Coloring on Comb-Convex and Caterpillar-Convex Bipartite Graphs. In Proceedings of the 29th International Computing and Combinatorics Conference (COCOON 2023) (168-181). https://doi.org/10.1007/978-3-031-49190-0_12

Given a graph G = (V, E) and a list of available colors L(v) for each vertex v ∈ V, where L(v) ⊆ {1, 2, . . . , k}, LIST k-COLORING refers to the problem of assigning colors to the vertices of G so that each vertex receives a color from its own list... Read More about List 3-Coloring on Comb-Convex and Caterpillar-Convex Bipartite Graphs.