DMVAE (Disentangled Multimodal VAE)10 uses a disentangled VAE approach to split up the private and shared (using PoE) latent spaces of multiple modalities, where the latent factor may be of both continuous and discrete nature. CADA (Cross- and Distribution Aligned)-VAE11 uses a cross-modal ...
文章目录Unsupervised Domain Adaptation via DisentangledRepresentations: Application to Cross-ModalityLiver Segmentation1.Author2.Abstract 3. Introduction 4. Methodology 4.1 DRLModule 4.2 Domain 智能推荐 Multimodal Routing: Improving Local and Global Interpretability of Multimodal Language Analysis阅读笔记 ...
if the cells across multimodalities do not have complete correspondence. However, this is an optional step if the cells across multimodalities have complete correspondence. In this study, we used Non-linear Manifold Alignment (NMA) [19] to align the unmatched ...
. We will show that our model is able to address both problems, thanks to its disentangled representation of content and style. Learning disentangled representations. Our work draws inspiration from recent works on disentangled representation learning. For example, InfoGAN ...
[MCM] Motion Consistency Model: Accelerating Video Diffusion with Disentangled Motion-Appearance Distillation (11 Jun 2024)Yuanhao Zhai, Kevin Lin, Zhengyuan Yang, et al.Yuanhao Zhai, Kevin Lin, Zhengyuan Yang, Linjie Li, Jianfeng Wang, Chung-Ching Lin, David Doermann, Junsong Yuan, Lijuan Wang...
IDE-3D: Interactive Disentangled Editing for High-Resolution 3D-aware Portrait Synthesis Jingxiang Sun, Xuan Wang, Yichun Shi, Lizhen Wang, Jue Wang, Yebin Liu SIGGRAPH Asia 2022 [Paper] [Code] [Project] Sem2NeRF: Converting Single-View Semantic Masks to Neural Radiance Fields ...
Learning Disentangled Representations.Our work draws inspiration from recent works on disentangled representation learning. For example, InfoGAN [57] andβ-VAE [58] have been proposed to learn disentangled representations without supervision. Some other works [59,60,61,62,63,64,65,66] focus on dise...
Wu Z Z, Lischinski D, Shechtman E. StyleSpace analysis: Disentangled controls for StyleGAN image generation. InProc. the 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition(CVPR), Jun. 2021, pp.12858–12867. DOI:https://doi.org/10.1109/cvpr46437.2021.01267. ...
In [16], the authors proposed the feature-disentangled activity recognition network (FDARN) for the cross-modal federated human activity recognition task. With five adversarial training modules, the proposed method captured both the modality-agnostic features and modality-specific discriminative characterist...
Unsupervised learning of disentangled and interpretable representations from sequential data. In Proceedings of the Advances in Neural Information Processing Systems, Long Beach, CA, USA, 4–9 December 2017; pp. 1878–1889. [Google Scholar] Saito, Y.; Ijima, Y.; Nishida, K.; Takamichi, S. ...