[CV] VideoBooth: Diffusion-based Video Generation with Image Prompts O网页链接 研究了一种新的视频生成任务,用图像提示生成视频。提出VideoBooth框架来解决该任务。VideoBooth使用两层的视觉嵌入来表达图像提示中的视觉特征。第一层是粗粒度的视觉嵌入,使用预训练的CLIP图像编码器提取图像特征,然后用MLP将特征映射...
论文翻译(扩散模型来了):Diffusion-Based Mel-Spectrogram Enhancement for Personalized Speech Synthesis with Found Data 利用发现的数据来创建合成声音是具有挑战性的,因为现实世界的录音通常包含各种类型的音频退化。解决这个问题的一种方法是使用增强模型对语音进行预增强,然后使用增强后的数据进行文本转语音(TTS)模型训...
https://www.youtube.com/watch?v=G3u5R4zYLNs DiPPeST: Diffusion-based Path Planner for Synthesizing Trajectories Applied on Quadruped Robots Maria Stamatopoulou, Jianwei Liu, Dimitrios Kanoulas We present DiPPeST, a novel image and goal conditioned diffusion-based trajectory generator for quadrupedal...
In this section, we provide a brief overview of TSDiff, an ML model designed to learn the conditional distribution of 3D TS geometries given 2D reaction information presented as SMARTS55(see Fig.1a). TSDiff is based on the stochastic denoising diffusion method, where the model is trained to ...
VideoBooth: Diffusion-based Video Generation with Image Prompts Yuming Jiang,Tianxing Wu,Shuai Yang,Chenyang Si,Dahua Lin,Yu Qiao,Chen Change Loy,Ziwei Liu FromMMLab@NTUaffliated with S-Lab, Nanyang Technological University and Shanghai AI Laboratory. ...
Diffusion-based models have recently demonstrated notable success in various generative tasks involving continuous signals, such as image, video, and audio synthesis. However, their applicability to video captioning has not yet received widespread attention, primarily due to the discrete nature of captions...
Faster Non-Log-Concave Sampling via Diffusion-based Monte Carlo Abstract: Efficient sampling from complex non-log-concave distributions is a cornerstone of statistical computing and machine learning, yet it is challenged by stringe...
In our survey, we systematically and comprehensively review on diffusion-based graph generative methods. We first make a review on three mainstream paradigms of diffusion methods, which are denoising diffusion probabilistic models, score-based genrative models, and stochastic differential equations. Then ...
Jouffroy, J., Opderbecke, J.: Underwater navigation using diffusion-based trajectory observers. IEEE J. Oceanic Eng. 32, 313-326 (2007)Jouffroy, J. and Opderbecke, J. Underwater navigation using diffusion-based trajectory observers. IEEE Journal of Oceanic Engineering, 2007. 32(2):313- ...
ABSTRACT Diffusion-Based Placement Migration Placement migration is the movement of cells within an existing placement to address a variety of post-placement design closure issues, such as timing, routing congestion, signal integrity, and heat distribution. To fix a design problem,... H Ren,I ...