2025年2月17日 · Abstract: In this paper, we propose the Dynamic Latent Frame Rate VAE (DLFR-VAE), a training-free paradigm that can make use of adaptive temporal compression in …

2025年3月6日 · Follow me for fishing reports, waypoints, and other information that can help make your day on the lake a success! Connect via Facebook, Instagram, or email. Read on for …

Dual-Level Feature Restoration (DLFR). Unlike the standalone implicit low-level feature reconstruction in TFR-Net, DLFR combines both implicit low-level feature reconstruction and …

Dynamic Latent Frame Rate VAE (DLFR-VAE) is a training-free paradigm that utilizes adaptive temporal compression in latent space. While existing video generative models apply fixed …

2022年8月16日 · In this paper, we propose a generic and unified framework to address them, named Efficient Multimodal Transformer with Dual-Level Feature Restoration (EMT-DLFR). …

2024年1月4日 · DLFR核心：结合隐式低层次特征重构（implicit low-level feature reconstruction）和显式高层次特征吸引（explict high-level feature attraction）。 融合过程： …

In this paper, we propose a generic and unified framework to address them, named Efficient Multimodal Transformer with Dual-Level Feature Restoration (EMT-DLFR). Concretely, EMT …

2025年2月17日 · In this paper, we propose the Dynamic Latent Frame Rate VAE (DLFR-VAE), a training-free paradigm that can make use of adaptive temporal compression in latent space. …

2023年6月12日 · 其中DLFR: 在incomplete modality setting中增加模型鲁棒性，使用DLFR – low-level feature reconstruction：用来implicitly鼓励模型从incomplete data中学习semantic …

EMT-DLFR aims to address the inefficiency in fusing unaligned multimodal sequences and the vulnerability to missing data in real-world scenarios to achieve efficient and robust multimodal …