a transformer-based Diffusion Planner for closed-loop planning. Introdcution 基于规则的规划方法通过定义驾驶行为边界并融入人类先验知识,已在工业级应用中取得初步成功(Fan et al., 2018),然而这类方法对预设规则的依赖导致其在新兴交通场景中的适应性受限(Hawke et al., 2020
图像的visual feature tokens和prompt的caption tokens之间的cross-attention(UNet中和SpatialTransformer或其子类参与计算的模块) \boldsymbol{v}=\boldsymbol{v}+\text{CrossAttn}(\boldsymbol{v},\boldsymbol{h}^c)\\为了加入Grounding条件,作者采用的是冻结上述两个注意力层,并且在它们中间加入一个新的 gated sel...
Then, in the second stage, a diffusion transformer is trained to generate motion sequences directly from audio cues, independent of character identity. Finally, a generator trained in the first stage uses the 3D facial representation and the generated motion sequences as inputs to render high-...
Writers: Ce Zheng, Guo-Jun Qi, Chen Chen PDF:DDT: A Diffusion-Driven Transformer-based Framework for Human Mesh Recovery from a Video Abstract Human mesh recovery (HMR) provides rich human body information for various real-world applications such as gaming, human-computer interaction, and virtual...
Zhao, C., Dong, C., Cai, W.: Learning a physical-aware diffusion model based on transformer for underwater image enhancement. Preprint arXiv:2403.01497 (2024) Jiang, H., Luo, A., Fan, H., Han, S., Liu, S.: Low-light image enhancement with wavelet-based diffusion models. ACM Tran...
C2F-DFT Learning A Coarse-to-Fine Diffusion Transformer for Image Restoration Liyan Wang Supervised Preprint' 2023 Image Restoration Diff-Plugin Diff-Plugin: Revitalizing Details for Diffusion-based Low-level tasks Yuhao Liu Supervised CVPR 2024 All-in-one Restoration DDPG Image Restoration by Denoi...
St-gan: Spatial transformer generative ad- versarial networks for image compositing. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pages 9455–9464, 2018. 2 [41] Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Pe...
Our contribution introduces a novel diffusion-based model coupled with a State Space Augmented Transformer. This synthesizes conditional 12-lead electrocardiograms based on the 12 multilabeled heart rhythm classes of the PTB-XL dataset, with each lead depicting the heart's electrical activity from ...
Deep learning-based image fusion methods can be further divided into CNN-based methods, Transformer-based methods, and image generation-based methods. In the field of image generation, GAN-based methods suffer from some issues such as training instability and mode collapse [7]. In recent years,...
这篇文章[1]采用了 conditional diffusion model 来做时间序列的 imputation 以及 forecasting 任务。本文的亮点在于,diffusion model 的网络结构不再是 CSDI[2] 中的transformer 结构,而是 structured state-space model(SSM)。我们可以把这种结构理解为 RNN、一维 CNN 以及transformer 的平替结构,都是 seq-to-seq 模...